How to use save method in avocado

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saver_test.py

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...90 "v0": v0,91 "v1": v1,92 "v2": v2.saveable93 }, restore_sequentially=True)94 val = save.save(sess, save_path)95 self.assertTrue(isinstance(val, six.string_types))96 self.assertEqual(save_path, val)97 # Start a second session. In that session the parameter nodes98 # have not been initialized either.99 with self.test_session(graph=ops_lib.Graph()) as sess:100 v0 = variable_op(-1.0, name="v0")101 v1 = variable_op(-1.0, name="v1")102 v2 = saver_test_utils.CheckpointedOp(name="v2")103 # Assert that the variables are not initialized.104 if context.in_graph_mode():105 self.assertEqual(106 len(variables.report_uninitialized_variables().eval()), 2)107 self.assertEqual(0, len(v2.keys().eval()))108 self.assertEqual(0, len(v2.values().eval()))109 # Restore the saved values in the parameter nodes.110 save = saver_module.Saver({"v0": v0, "v1": v1, "v2": v2.saveable})111 save.restore(sess, save_path)112 # Check that the parameter nodes have been restored.113 self.assertEqual(10.0, self.evaluate(v0))114 self.assertEqual(20.0, self.evaluate(v1))115 self.assertEqual(b"k1", self.evaluate(v2.keys()))116 self.assertEqual(30.0, self.evaluate(v2.values()))117 # Build another graph with 2 nodes, initialized118 # differently, and a Restore node for them.119 with self.test_session(graph=ops_lib.Graph()) as sess:120 v0_2 = variable_op(1000.0, name="v0")121 v1_2 = variable_op(2000.0, name="v1")122 v2_2 = saver_test_utils.CheckpointedOp(name="v2")123 v2_init = v2_2.insert("k1000", 3000.0)124 # Check that the parameter nodes have been initialized.125 if context.in_graph_mode():126 init_all_op = [variables.global_variables_initializer(), v2_init]127 self.evaluate(init_all_op)128 # TODO(xpan): Why _mutable_hash_table_v2 doesn't create empty129 # table as it claims in eager mode?130 self.assertEqual(b"k1000", self.evaluate(v2_2.keys()))131 self.assertEqual(3000.0, self.evaluate(v2_2.values()))132 self.assertEqual(1000.0, self.evaluate(v0_2))133 self.assertEqual(2000.0, self.evaluate(v1_2))134 # Restore the values saved earlier in the parameter nodes.135 save2 = saver_module.Saver({"v0": v0_2, "v1": v1_2, "v2": v2_2.saveable})136 save2.restore(sess, save_path)137 # Check that the parameter nodes have been restored.138 self.assertEqual(10.0, self.evaluate(v0_2))139 self.assertEqual(20.0, self.evaluate(v1_2))140 self.assertEqual(b"k1", self.evaluate(v2_2.keys()))141 self.assertEqual(30.0, self.evaluate(v2_2.values()))142 def testBasic(self):143 self.basicSaveRestore(variables.Variable)144 @test_util.run_in_graph_and_eager_modes()145 def testResourceBasic(self):146 self.basicSaveRestore(resource_variable_ops.ResourceVariable)147 def testEagerBasic(self):148 with context.eager_mode():149 ckpt_prefix = os.path.join(self.get_temp_dir(), "ckpt")150 v1 = resource_variable_ops.ResourceVariable(3.14, name="v1")151 v2 = resource_variable_ops.ResourceVariable([1, 2], name="v2")152 save = saver_module.Saver([v1, v2])153 save.save(None, ckpt_prefix)154 v1.assign(0.0)155 v2.assign([0, 0])156 self.assertNear(0.0, self.evaluate(v1), 1e-5)157 self.assertAllEqual([0, 0], self.evaluate(v2))158 save.restore(None, ckpt_prefix)159 self.assertNear(3.14, self.evaluate(v1), 1e-5)160 self.assertAllEqual([1, 2], self.evaluate(v2))161 def testEagerGraphCompatibility(self):162 # Save from graph mode and restore from eager mode.163 graph_ckpt_prefix = os.path.join(self.get_temp_dir(), "graph_ckpt")164 with context.graph_mode():165 with self.test_session(graph=ops_lib.Graph()) as sess:166 # Create a graph model and save the checkpoint.167 w1 = resource_variable_ops.ResourceVariable(1.0, name="w1")168 w2 = resource_variable_ops.ResourceVariable(2.0, name="w2")169 graph_saver = saver_module.Saver([w1, w2])170 sess.run(variables.global_variables_initializer())171 graph_saver.save(sess, graph_ckpt_prefix)172 with context.eager_mode():173 ops_lib._default_graph_stack.reset() # pylint: disable=protected-access174 ops_lib.reset_default_graph()175 w1 = resource_variable_ops.ResourceVariable(0.0, name="w1")176 w2 = resource_variable_ops.ResourceVariable(0.0, name="w2")177 graph_saver = saver_module.Saver([w1, w2])178 graph_saver.restore(None, graph_ckpt_prefix)179 self.assertAllEqual(self.evaluate(w1), 1.0)180 self.assertAllEqual(self.evaluate(w2), 2.0)181 # Save from eager mode and restore from graph mode.182 eager_ckpt_prefix = os.path.join(self.get_temp_dir(), "eager_ckpt")183 with context.eager_mode():184 ops_lib._default_graph_stack.reset() # pylint: disable=protected-access185 ops_lib.reset_default_graph()186 w3 = resource_variable_ops.ResourceVariable(3.0, name="w3")187 w4 = resource_variable_ops.ResourceVariable(4.0, name="w4")188 graph_saver = saver_module.Saver([w3, w4])189 graph_saver.save(None, eager_ckpt_prefix)190 with context.graph_mode():191 with self.test_session(graph=ops_lib.Graph()) as sess:192 w3 = resource_variable_ops.ResourceVariable(0.0, name="w3")193 w4 = resource_variable_ops.ResourceVariable(0.0, name="w4")194 graph_saver = saver_module.Saver([w3, w4])195 sess.run(variables.global_variables_initializer())196 graph_saver.restore(sess, eager_ckpt_prefix)197 self.assertAllEqual(w3.eval(), 3.0)198 self.assertAllEqual(w4.eval(), 4.0)199 @test_util.run_in_graph_and_eager_modes()200 def testResourceSaveRestoreCachingDevice(self):201 save_path = os.path.join(self.get_temp_dir(), "resource_cache")202 with self.test_session(graph=ops_lib.Graph()) as sess:203 v = resource_variable_ops.ResourceVariable([1], caching_device="/​cpu:0",204 name="v")205 if context.in_graph_mode():206 self.evaluate(variables.global_variables_initializer())207 else:208 sess = None209 save = saver_module.Saver([v])210 save.save(sess, save_path)211 save2 = saver_module.Saver([v])212 save2.restore(sess, save_path)213 self.assertEquals(self.evaluate(v), [1])214 def testSaveCopyRestoreWithSaveRelativePaths(self):215 """Save, copy checkpoint dir and restore from copied dir.216 This only works for save_relative_paths=True.217 """218 save_dir1 = os.path.join(self.get_temp_dir(), "save_dir1")219 os.mkdir(save_dir1)220 save_path1 = os.path.join(save_dir1, "save_copy_restore")221 # Build a graph with 2 parameter nodes, and Save and222 # Restore nodes for them.223 v0 = variables.Variable(10.0, name="v0")224 v1 = variables.Variable(20.0, name="v1")225 v2 = saver_test_utils.CheckpointedOp(name="v2")226 v2_init = v2.insert("k1", 30.0)227 save = saver_module.Saver(228 var_list={229 "v0": v0,230 "v1": v1,231 "v2": v2.saveable},232 restore_sequentially=True,233 save_relative_paths=True)234 init_all_op = [variables.global_variables_initializer(), v2_init]235 with self.test_session() as sess:236 # Initialize all variables237 sess.run(init_all_op)238 # Check that the parameter nodes have been initialized.239 self.assertEqual(10.0, v0.eval())240 self.assertEqual(20.0, v1.eval())241 self.assertEqual(b"k1", v2.keys().eval())242 self.assertEqual(30.0, v2.values().eval())243 # Save the initialized values in the file at "save_path"244 val = save.save(sess, save_path1)245 self.assertTrue(isinstance(val, six.string_types))246 self.assertEqual(save_path1, val)247 self.assertEqual(saver_module.latest_checkpoint(save_dir1), save_path1)248 save_dir2 = os.path.join(self.get_temp_dir(), "save_dir2")249 os.renames(save_dir1, save_dir2)250 save_path2 = os.path.join(save_dir2, "save_copy_restore")251 self.assertEqual(saver_module.latest_checkpoint(save_dir2), save_path2)252 # Start a second session. In that session the parameter nodes253 # have not been initialized either.254 with self.test_session() as sess:255 v0 = variables.Variable(-1.0, name="v0")256 v1 = variables.Variable(-1.0, name="v1")257 v2 = saver_test_utils.CheckpointedOp(name="v2")258 save = saver_module.Saver({"v0": v0, "v1": v1, "v2": v2.saveable})259 # Assert that the variables are not initialized.260 self.assertEqual(261 len(variables.report_uninitialized_variables().eval()), 2)262 self.assertEqual(0, len(v2.keys().eval()))263 self.assertEqual(0, len(v2.values().eval()))264 # Restore the saved values in the parameter nodes.265 save.restore(sess, save_path2)266 # Check that the parameter nodes have been restored.267 self.assertEqual(10.0, v0.eval())268 self.assertEqual(20.0, v1.eval())269 self.assertEqual(b"k1", v2.keys().eval())270 self.assertEqual(30.0, v2.values().eval())271 def testFilenameTensor(self):272 v0 = variables.Variable(0, name="v0")273 filename = b"somerandomfilename"274 save = saver_module.Saver({"v0": v0}, filename=filename)275 with self.test_session() as sess:276 tensor = sess.graph.get_tensor_by_name(277 save.saver_def.filename_tensor_name)278 self.assertEqual(sess.run(tensor), filename)279 def testInvalidPath(self):280 v0 = variables.Variable(0, name="v0")281 for ver in (saver_pb2.SaverDef.V1, saver_pb2.SaverDef.V2):282 with self.test_session() as sess:283 save = saver_module.Saver({"v0": v0}, write_version=ver)284 with self.assertRaisesRegexp(errors.NotFoundError,285 "Failed to find any matching files for"):286 save.restore(sess, "invalid path")287 def testInt64(self):288 save_path = os.path.join(self.get_temp_dir(), "int64")289 with self.test_session() as sess:290 # Build a graph with 1 node, and save and restore for them.291 v = variables.Variable(np.int64(15), name="v")292 save = saver_module.Saver({"v": v}, restore_sequentially=True)293 variables.global_variables_initializer().run()294 # Save the initialized values in the file at "save_path"295 val = save.save(sess, save_path)296 self.assertTrue(isinstance(val, six.string_types))297 self.assertEqual(save_path, val)298 with self.test_session() as sess:299 v = variables.Variable(np.int64(-1), name="v")300 save = saver_module.Saver({"v": v})301 with self.assertRaisesWithPredicateMatch(302 errors_impl.OpError, lambda e: "uninitialized value v" in e.message):303 sess.run(v)304 # Restore the saved values in the parameter nodes.305 save.restore(sess, save_path)306 # Check that the parameter nodes have been restored.307 self.assertEqual(np.int64(15), v.eval())308 def testSomeErrors(self):309 with ops_lib.Graph().as_default():310 v0 = variables.Variable([10.0], name="v0")311 v1 = variables.Variable([20.0], name="v1")312 v2 = variables.Variable([20.0], name="v2")313 v2._set_save_slice_info(314 variables.Variable.SaveSliceInfo("v1", [1], [0], [1]))315 # By default the name used for "v2" will be "v1" and raise an error.316 with self.assertRaisesRegexp(ValueError, "same name: v1"):317 saver_module.Saver([v0, v1, v2])318 # The names are different and will work.319 saver_module.Saver({"vee1": v1, "other": [v2]})320 # Partitioned variables also cause name conflicts.321 p_v1 = variable_scope.get_variable(322 "p_v1",323 shape=[4, 5],324 partitioner=partitioned_variables.fixed_size_partitioner(325 num_shards=2))326 p_v2 = variable_scope.get_variable(327 "p_v2",328 shape=[4, 5],329 partitioner=partitioned_variables.fixed_size_partitioner(330 num_shards=2))331 p_v2._name = "p_v1"332 with self.assertRaisesRegexp(ValueError, "same name: p_v1"):333 saver_module.Saver([p_v1, p_v2])334 def testSameName(self):335 with ops_lib.Graph().as_default():336 v0 = variables.Variable([10.0], name="v0")337 v2 = saver_test_utils.CheckpointedOp(name="v2")338 # Saving one variable under two names raises an error.339 with self.assertRaisesRegexp(340 ValueError, "The same saveable will be restored with two names: v0"):341 saver_module.Saver({"v0": v0, "v0too": v0})342 # Ditto for custom saveables.343 with self.assertRaisesRegexp(344 ValueError, "The same saveable will be restored with two names: v2"):345 saver_module.Saver({"v2": v2.saveable, "v2too": v2.saveable})346 # Verify non-duplicate names work.347 saver_module.Saver({"v0": v0, "v2": v2.saveable})348 def testBasicsWithListOfVariables(self):349 save_path = os.path.join(self.get_temp_dir(), "basics_with_list")350 with self.test_session(graph=ops_lib.Graph()) as sess:351 # Build a graph with 2 parameter nodes, and Save and352 # Restore nodes for them.353 v0 = variables.Variable(10.0, name="v0")354 v1 = variables.Variable(20.0, name="v1")355 v2 = saver_test_utils.CheckpointedOp(name="v2")356 v2_init = v2.insert("k1", 30.0)357 save = saver_module.Saver([v0, v1, v2.saveable])358 variables.global_variables_initializer().run()359 v2_init.run()360 # Check that the parameter nodes have been initialized.361 self.assertEqual(10.0, v0.eval())362 self.assertEqual(20.0, v1.eval())363 self.assertEqual(b"k1", v2.keys().eval())364 self.assertEqual(30.0, v2.values().eval())365 # Save the initialized values in the file at "save_path"366 val = save.save(sess, save_path)367 self.assertTrue(isinstance(val, six.string_types))368 self.assertEqual(save_path, val)369 # Start a second session. In that session the variables370 # have not been initialized either.371 with self.test_session(graph=ops_lib.Graph()) as sess:372 v0 = variables.Variable(-1.0, name="v0")373 v1 = variables.Variable(-1.0, name="v1")374 v2 = saver_test_utils.CheckpointedOp(name="v2")375 save = saver_module.Saver([v0, v1, v2.saveable])376 with self.assertRaisesWithPredicateMatch(377 errors_impl.OpError, lambda e: "uninitialized value v0" in e.message):378 sess.run(v0)379 with self.assertRaisesWithPredicateMatch(380 errors_impl.OpError, lambda e: "uninitialized value v1" in e.message):381 sess.run(v1)382 self.assertEqual(0, len(v2.keys().eval()))383 self.assertEqual(0, len(v2.values().eval()))384 # Restore the saved values in the parameter nodes.385 save.restore(sess, save_path)386 # Check that the parameter nodes have been restored.387 self.assertEqual(10.0, v0.eval())388 self.assertEqual(20.0, v1.eval())389 self.assertEqual(b"k1", v2.keys().eval())390 self.assertEqual(30.0, v2.values().eval())391 # Build another graph with 2 nodes, initialized392 # differently, and a Restore node for them.393 with self.test_session(graph=ops_lib.Graph()) as sess:394 v0_2 = variables.Variable(1000.0, name="v0")395 v1_2 = variables.Variable(2000.0, name="v1")396 v2_2 = saver_test_utils.CheckpointedOp(name="v2")397 save2 = saver_module.Saver([v0_2, v1_2, v2_2.saveable])398 v2_2.insert("k1000", 3000.0).run()399 variables.global_variables_initializer().run()400 # Check that the parameter nodes have been initialized.401 self.assertEqual(1000.0, v0_2.eval())402 self.assertEqual(2000.0, v1_2.eval())403 self.assertEqual(b"k1000", v2_2.keys().eval())404 self.assertEqual(3000.0, v2_2.values().eval())405 # Restore the values saved earlier in the parameter nodes.406 save2.restore(sess, save_path)407 # Check that the parameter nodes have been restored.408 self.assertEqual(10.0, v0_2.eval())409 self.assertEqual(20.0, v1_2.eval())410 self.assertEqual(b"k1", v2_2.keys().eval())411 self.assertEqual(30.0, v2_2.values().eval())412 def _SaveAndLoad(self, var_name, var_value, other_value, save_path):413 with self.test_session(graph=ops_lib.Graph()) as sess:414 var = resource_variable_ops.ResourceVariable(var_value, name=var_name)415 save = saver_module.Saver({var_name: var})416 if context.in_graph_mode():417 self.evaluate(var.initializer)418 val = save.save(sess, save_path)419 self.assertEqual(save_path, val)420 with self.test_session(graph=ops_lib.Graph()) as sess:421 var = resource_variable_ops.ResourceVariable(other_value, name=var_name)422 save = saver_module.Saver({var_name: var})423 save.restore(sess, save_path)424 self.assertAllClose(var_value, self.evaluate(var))425 def testCacheRereadsFile(self):426 save_path = os.path.join(self.get_temp_dir(), "cache_rereads")427 # Save and reload one Variable named "var0".428 self._SaveAndLoad("var0", 0.0, 1.0, save_path)429 # Save and reload one Variable named "var1" in the same file.430 # The cached readers should know to re-read the file.431 self._SaveAndLoad("var1", 1.1, 2.2, save_path)432 def testAllowEmpty(self):433 save_path = os.path.join(self.get_temp_dir(), "allow_empty")434 with self.test_session() as sess:435 _ = constant_op.constant(1)436 save = saver_module.Saver(allow_empty=True)437 val = save.save(sess, save_path)438 self.assertIsNone(val)439 with self.test_session() as sess:440 save = saver_module.Saver(allow_empty=True)441 save.restore(sess, save_path)442 def testGPU(self):443 if not test.is_gpu_available():444 return445 save_path = os.path.join(self.get_temp_dir(), "gpu")446 with session.Session("", graph=ops_lib.Graph()) as sess:447 with sess.graph.device(test.gpu_device_name()):448 v0_1 = variables.Variable(123.45)449 save = saver_module.Saver({"v0": v0_1})450 variables.global_variables_initializer().run()451 save.save(sess, save_path)452 with session.Session("", graph=ops_lib.Graph()) as sess:453 with sess.graph.device(test.gpu_device_name()):454 v0_2 = variables.Variable(543.21)455 save = saver_module.Saver({"v0": v0_2})456 variables.global_variables_initializer().run()457 def testVariables(self):458 save_path = os.path.join(self.get_temp_dir(), "variables")459 with session.Session("", graph=ops_lib.Graph()) as sess:460 one = variables.Variable(1.0)461 twos = variables.Variable([2.0, 2.0, 2.0])462 v2 = saver_test_utils.CheckpointedOp(name="v2")463 init = variables.global_variables_initializer()464 save = saver_module.Saver()465 init.run()466 v2.insert("k1", 3.0).run()467 save.save(sess, save_path)468 with session.Session("", graph=ops_lib.Graph()) as sess:469 one = variables.Variable(0.0)470 twos = variables.Variable([0.0, 0.0, 0.0])471 v2 = saver_test_utils.CheckpointedOp(name="v2")472 # Saver with no arg, defaults to 'all variables'.473 save = saver_module.Saver()474 save.restore(sess, save_path)475 self.assertAllClose(1.0, one.eval())476 self.assertAllClose([2.0, 2.0, 2.0], twos.eval())477 self.assertEqual(b"k1", v2.keys().eval())478 self.assertEqual(3.0, v2.values().eval())479 def testVarListShouldBeEmptyInDeferredBuild(self):480 with ops_lib.Graph().as_default():481 v = variables.Variable(1.0)482 with self.assertRaisesRegexp(ValueError, "defer_build"):483 saver_module.Saver([v], defer_build=True)484 def testBuildShouldBeCalledBeforeSaveInCaseOfDeferBuild(self):485 save_path = os.path.join(self.get_temp_dir(), "error_deferred_build")486 with ops_lib.Graph().as_default(), session.Session() as sess:487 variables.Variable(1.0)488 saver = saver_module.Saver(defer_build=True)489 with self.assertRaisesRegexp(RuntimeError, "build"):490 saver.save(sess, save_path)491 def testDeferredBuild(self):492 save_path = os.path.join(self.get_temp_dir(), "deferred_build")493 with session.Session("", graph=ops_lib.Graph()) as sess:494 one = variables.Variable(1.0)495 save = saver_module.Saver(defer_build=True)496 # if build is not deferred, saver cannot save the `twos`.497 twos = variables.Variable([2.0, 2.0, 2.0])498 init = variables.global_variables_initializer()499 save.build()500 init.run()501 save.save(sess, save_path)502 with session.Session("", graph=ops_lib.Graph()) as sess:503 one = variables.Variable(0.0)504 twos = variables.Variable([0.0, 0.0, 0.0])505 # Saver with no arg, defaults to 'all variables'.506 save = saver_module.Saver()507 save.restore(sess, save_path)508 self.assertAllClose(1.0, one.eval())509 self.assertAllClose([2.0, 2.0, 2.0], twos.eval())510 def testReshape(self):511 save_path = os.path.join(self.get_temp_dir(), "variables_reshape")512 with session.Session("", graph=ops_lib.Graph()) as sess:513 var = variables.Variable([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]])514 init = variables.global_variables_initializer()515 save = saver_module.Saver()516 init.run()517 save.save(sess, save_path)518 # Error when restoring with default reshape=False519 with session.Session("", graph=ops_lib.Graph()) as sess:520 var = variables.Variable([[0.0, 0.0], [0.0, 0.0], [0.0, 0.0]])521 save = saver_module.Saver()522 with self.assertRaisesRegexp(523 errors_impl.InvalidArgumentError,524 "Assign requires shapes of both tensors to match."):525 save.restore(sess, save_path)526 # Restored to new shape with reshape=True527 with session.Session("", graph=ops_lib.Graph()) as sess:528 var = variables.Variable([[0.0, 0.0], [0.0, 0.0], [0.0, 0.0]])529 save = saver_module.Saver(reshape=True)530 save.restore(sess, save_path)531 self.assertAllClose([[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]], var.eval())532 @test_util.run_in_graph_and_eager_modes()533 def testSaveWithGlobalStep(self, pad_step_number=False):534 save_path = os.path.join(self.get_temp_dir(), "ckpt_with_global_step")535 global_step_int = 5536 # Save and reload one Variable named "var0".537 self._SaveAndLoad("var0", 0.0, 1.0, save_path)538 for use_tensor in [True, False]:539 with self.test_session(graph=ops_lib.Graph()):540 var = resource_variable_ops.ResourceVariable(1.0, name="var0")541 save = saver_module.Saver(542 {543 var._shared_name: var544 }, pad_step_number=pad_step_number)545 if context.in_graph_mode():546 self.evaluate(var.initializer)547 sess = ops_lib.get_default_session()548 else:549 sess = None550 if use_tensor:551 global_step = constant_op.constant(global_step_int)552 val = save.save(sess, save_path, global_step=global_step)553 else:554 val = save.save(sess, save_path, global_step=global_step_int)555 if pad_step_number:556 expected_save_path = "%s-%s" % (save_path,557 "{:08d}".format(global_step_int))558 else:559 expected_save_path = "%s-%d" % (save_path, global_step_int)560 self.assertEqual(expected_save_path, val)561 def testSaveWithGlobalStepWithPadding(self):562 self.testSaveWithGlobalStep(pad_step_number=True)563 def testSaveToNonexistingPath(self):564 file_io.write_string_to_file(565 os.path.join(self.get_temp_dir(), "actually_a_file"), "")566 paths = [567 os.path.join(self.get_temp_dir(), "nonexisting_dir/​path"),568 os.path.join(self.get_temp_dir(), "other_nonexisting_dir/​path1/​path2"),569 os.path.join(self.get_temp_dir(), "actually_a_file/​path"),570 ]571 for save_path in paths:572 # Build a graph with 2 parameter nodes, and Save and573 # Restore nodes for them.574 v0 = variables.Variable(10.0, name="v0")575 v1 = variables.Variable(20.0, name="v1")576 save = saver_module.Saver({"v0": v0, "v1": v1}, restore_sequentially=True)577 init_all_op = variables.global_variables_initializer()578 # In the case where the parent directory doesn't exist, whether or not the579 # save succeeds or fails is implementation dependent. Therefore we allow580 # both cases.581 try:582 with self.test_session() as sess:583 # Initialize all variables584 sess.run(init_all_op)585 # Check that the parameter nodes have been initialized.586 self.assertEqual(10.0, v0.eval())587 self.assertEqual(20.0, v1.eval())588 # Save the graph.589 save.save(sess, save_path)590 with self.test_session() as sess:591 # Restore the saved values in the parameter nodes.592 save.restore(sess, save_path)593 # Check that the parameter nodes have been restored.594 self.assertEqual(10.0, v0.eval())595 self.assertEqual(20.0, v1.eval())596 except ValueError as exc:597 error_msg_template = "Parent directory of {} doesn't exist, can't save."598 self.assertEqual(error_msg_template.format(save_path), str(exc))599 def testSaveToURI(self):600 # ParseURI functions don't work on Windows yet.601 # TODO(jhseu): Remove this check when it works.602 if os.name == "nt":603 self.skipTest("Local URI support doesn't work on Windows")604 save_path = "file:/​/​" + os.path.join(self.get_temp_dir(), "uri")605 # Build a graph with 2 parameter nodes, and Save and606 # Restore nodes for them.607 v0 = variables.Variable(10.0, name="v0")608 v1 = variables.Variable(20.0, name="v1")609 save = saver_module.Saver({"v0": v0, "v1": v1}, restore_sequentially=True)610 init_all_op = variables.global_variables_initializer()611 with self.test_session() as sess:612 # Initialize all variables613 sess.run(init_all_op)614 # Check that the parameter nodes have been initialized.615 self.assertEqual(10.0, v0.eval())616 self.assertEqual(20.0, v1.eval())617 save.save(sess, save_path)618class SaveRestoreShardedTest(test.TestCase):619 def _get_test_dir(self, dirname):620 test_dir = os.path.join(self.get_temp_dir(), dirname)621 gfile.MakeDirs(test_dir)622 return test_dir623 def testBasics(self):624 save_path = os.path.join(self.get_temp_dir(), "sharded_basics")625 # Build a graph with 2 parameter nodes on different devices.626 with session.Session(627 target="",628 config=config_pb2.ConfigProto(device_count={"CPU": 2})) as sess:629 with sess.graph.device("/​cpu:0"):630 v0 = variables.Variable(10, name="v0")631 t0 = saver_test_utils.CheckpointedOp(name="t0")632 with sess.graph.device("/​cpu:1"):633 v1 = variables.Variable(20, name="v1")634 t1 = saver_test_utils.CheckpointedOp(name="t1")635 save = saver_module.Saver(636 {637 "v0": v0,638 "v1": v1,639 "t0": t0.saveable,640 "t1": t1.saveable641 },642 sharded=True)643 variables.global_variables_initializer().run()644 t0.insert("k1", 30.0).run()645 t1.insert("k2", 40.0).run()646 val = save.save(sess, save_path)647 if save._write_version is saver_pb2.SaverDef.V1:648 self.assertEqual(save_path + "-?????-of-00002", val)649 else:650 self.assertEqual(save_path, val)651 meta_graph_filename = save._MetaGraphFilename(val)652 self.assertEqual(save_path + ".meta", meta_graph_filename)653 if save._write_version is saver_pb2.SaverDef.V1:654 # Restore different ops from shard 0 of the saved files.655 with session.Session(656 target="",657 config=config_pb2.ConfigProto(device_count={"CPU": 2})) as sess:658 with sess.graph.device("/​cpu:0"):659 v0 = variables.Variable(111, name="v0")660 t0 = saver_test_utils.CheckpointedOp(name="t0")661 save = saver_module.Saver({"v0": v0, "t0": t0.saveable}, sharded=True)662 variables.global_variables_initializer().run()663 t0.insert("k11", 33.0).run()664 self.assertEqual(111, v0.eval())665 self.assertEqual(b"k11", t0.keys().eval())666 self.assertEqual(33.0, t0.values().eval())667 save.restore(sess, save_path + "-00000-of-00002")668 self.assertEqual(10, v0.eval())669 self.assertEqual(b"k1", t0.keys().eval())670 self.assertEqual(30.0, t0.values().eval())671 # Restore different ops from shard 1 of the saved files.672 with session.Session(673 target="",674 config=config_pb2.ConfigProto(device_count={"CPU": 2})) as sess:675 with sess.graph.device("/​cpu:0"):676 v1 = variables.Variable(222)677 t1 = saver_test_utils.CheckpointedOp(name="t1")678 save = saver_module.Saver({"v1": v1, "t1": t1.saveable}, sharded=True)679 variables.global_variables_initializer().run()680 t1.insert("k22", 44.0).run()681 self.assertEqual(222, v1.eval())682 self.assertEqual(b"k22", t1.keys().eval())683 self.assertEqual(44.0, t1.values().eval())684 save.restore(sess, save_path + "-00001-of-00002")685 self.assertEqual(20, v1.eval())686 self.assertEqual(b"k2", t1.keys().eval())687 self.assertEqual(40.0, t1.values().eval())688 # Now try a restore with the sharded filename.689 with session.Session(690 target="",691 config=config_pb2.ConfigProto(device_count={"CPU": 2})) as sess:692 with sess.graph.device("/​cpu:0"):693 v0 = variables.Variable(111, name="v0")694 t0 = saver_test_utils.CheckpointedOp(name="t0")695 with sess.graph.device("/​cpu:1"):696 v1 = variables.Variable(222, name="v1")697 t1 = saver_test_utils.CheckpointedOp(name="t1")698 save = saver_module.Saver(699 {700 "v0": v0,701 "v1": v1,702 "t0": t0.saveable,703 "t1": t1.saveable704 },705 sharded=True)706 variables.global_variables_initializer().run()707 t0.insert("k11", 33.0).run()708 t1.insert("k22", 44.0).run()709 self.assertEqual(111, v0.eval())710 self.assertEqual(222, v1.eval())711 self.assertEqual(b"k11", t0.keys().eval())712 self.assertEqual(33.0, t0.values().eval())713 self.assertEqual(b"k22", t1.keys().eval())714 self.assertEqual(44.0, t1.values().eval())715 save_path = os.path.join(self.get_temp_dir(), "sharded_basics")716 if save._write_version is saver_pb2.SaverDef.V1:717 save.restore(sess, save_path + "-?????-of-?????")718 else:719 save.restore(sess, save_path)720 self.assertEqual(10, v0.eval())721 self.assertEqual(20, v1.eval())722 self.assertEqual(b"k1", t0.keys().eval())723 self.assertEqual(30.0, t0.values().eval())724 self.assertEqual(b"k2", t1.keys().eval())725 self.assertEqual(40.0, t1.values().eval())726 if save._write_version is saver_pb2.SaverDef.V1:727 self.assertEqual(728 saver_module.latest_checkpoint(self.get_temp_dir()),729 os.path.join(self.get_temp_dir(), "sharded_basics-?????-of-00002"))730 else:731 self.assertEqual(732 saver_module.latest_checkpoint(self.get_temp_dir()),733 os.path.join(self.get_temp_dir(), "sharded_basics"))734 def testSaverDef(self):735 with self.test_session():736 v0 = variables.Variable(123, name="v0")737 save = saver_module.Saver({"v0": v0}, sharded=True)738 sd = save.as_saver_def()739 self.assertTrue(sd.sharded)740 def _testPartitionedVariables(self, use_resource):741 var_full_shape = [10, 3]742 # Allows save/​restore mechanism to work w/​ different slicings.743 var_name = "my_var"744 saved_dir = self._get_test_dir("partitioned_variables")745 saved_path = os.path.join(saved_dir, "ckpt")746 call_saver_with_dict = False # updated by test loop below747 def _save(slices=None, partitioner=None):748 with self.test_session(graph=ops_lib.Graph()) as sess:749 # Calls .eval() to return the ndarray that makes up the full variable.750 rnd = random_ops.random_uniform(var_full_shape).eval()751 if slices:752 assert not partitioner753 # TODO(apassos): make create_partitioned_variables take use_resource754 # option to make this test passable without creating a named755 # variable_scope.756 vs = partitioned_variables.create_partitioned_variables(757 var_full_shape, slices, rnd, name=var_name)758 elif partitioner:759 vs = [760 variable_scope.get_variable(761 var_name,762 shape=var_full_shape,763 initializer=rnd,764 partitioner=partitioner,765 use_resource=use_resource)766 ]767 else:768 if use_resource:769 vs = [resource_variable_ops.ResourceVariable(rnd, name=var_name)]770 else:771 vs = [variables.Variable(rnd, name=var_name)]772 variables.global_variables_initializer().run()773 if call_saver_with_dict:774 saver = saver_module.Saver({var_name: (vs if slices else vs[0])})775 else:776 saver = saver_module.Saver(vs)777 actual_path = saver.save(sess, saved_path)778 self.assertEqual(saved_path, actual_path)779 return rnd780 def _restore(slices=None, partitioner=None):781 with self.test_session(graph=ops_lib.Graph()) as sess:782 if slices:783 assert not partitioner784 new_vs = partitioned_variables.create_partitioned_variables(785 var_full_shape,786 slices,787 array_ops.zeros(var_full_shape), # != original contents.788 name=var_name)789 elif partitioner:790 new_vs = [791 variable_scope.get_variable(792 var_name,793 shape=var_full_shape,794 initializer=array_ops.zeros(var_full_shape),795 partitioner=partitioner)796 ]797 else:798 new_vs = [799 variables.Variable(800 array_ops.zeros(801 shape=var_full_shape), # != original contents.802 name=var_name)803 ]804 variables.global_variables_initializer().run()805 if call_saver_with_dict:806 saver = saver_module.Saver({807 var_name: (new_vs if slices else new_vs[0])808 })809 else:810 saver = saver_module.Saver(new_vs)811 saver.restore(sess, saved_path)812 if partitioner:813 return new_vs[0].as_tensor().eval()814 elif slices and slices[0] != 1:815 return array_ops.concat(new_vs, 0).eval()816 elif slices and slices[1] != 1:817 return array_ops.concat(new_vs, 1).eval()818 else: # Non-sliced.819 return new_vs[0].eval()820 for call_saver_with_dict in {False, True}:821 # Save PartitionedVariable and restore into full variable.822 saved_full = _save(823 partitioner=partitioned_variables.fixed_size_partitioner(824 num_shards=2))825 restored_full = _restore()826 self.assertAllEqual(saved_full, restored_full)827 # Saves 10 horizontal parts of a partitioned variable.828 # Restores into a full variable, non-sliced.829 saved_full = _save(slices=[10, 1])830 restored_full = _restore()831 self.assertAllEqual(saved_full, restored_full)832 # Restores into a different number/​orientation of slices.833 restored_full = _restore(slices=[2, 1]) # 2 horizon parts.834 self.assertAllEqual(saved_full, restored_full)835 restored_full = _restore(slices=[1, 3]) # 3 vertical parts.836 self.assertAllEqual(saved_full, restored_full)837 # Restores into a PartitionedVariable838 restored_full = _restore(839 partitioner=partitioned_variables.fixed_size_partitioner(840 num_shards=2))841 self.assertAllEqual(saved_full, restored_full)842 # Now, saves a full variable and restores in slices.843 saved_full = _save()844 restored_full = _restore(slices=[1, 3])845 self.assertAllEqual(saved_full, restored_full)846 def testPartitionedVariable(self):847 self._testPartitionedVariables(use_resource=False)848 def testPartitionedResourceVariable(self):849 self._testPartitionedVariables(use_resource=True)850class MaxToKeepTest(test.TestCase):851 def _get_test_dir(self, dirname):852 test_dir = os.path.join(self.get_temp_dir(), dirname)853 gfile.MakeDirs(test_dir)854 return test_dir855 def assertCheckpointState(self, model_checkpoint_path,856 all_model_checkpoint_paths, save_dir):857 checkpoint_state = saver_module.get_checkpoint_state(save_dir)858 self.assertEqual(checkpoint_state.model_checkpoint_path,859 model_checkpoint_path)860 self.assertEqual(checkpoint_state.all_model_checkpoint_paths,861 all_model_checkpoint_paths)862 def testNonSharded(self):863 save_dir = self._get_test_dir("max_to_keep_non_sharded")864 with self.test_session() as sess:865 v = variables.Variable(10.0, name="v")866 save = saver_module.Saver({"v": v}, max_to_keep=2)867 variables.global_variables_initializer().run()868 self.assertEqual([], save.last_checkpoints)869 s1 = save.save(sess, os.path.join(save_dir, "s1"))870 self.assertEqual([s1], save.last_checkpoints)871 self.assertTrue(saver_module.checkpoint_exists(s1))872 self.assertCheckpointState(873 model_checkpoint_path=s1,874 all_model_checkpoint_paths=[s1],875 save_dir=save_dir)876 s2 = save.save(sess, os.path.join(save_dir, "s2"))877 self.assertEqual([s1, s2], save.last_checkpoints)878 self.assertTrue(saver_module.checkpoint_exists(s1))879 self.assertTrue(saver_module.checkpoint_exists(s2))880 self.assertCheckpointState(881 model_checkpoint_path=s2,882 all_model_checkpoint_paths=[s1, s2],883 save_dir=save_dir)884 s3 = save.save(sess, os.path.join(save_dir, "s3"))885 self.assertEqual([s2, s3], save.last_checkpoints)886 self.assertFalse(saver_module.checkpoint_exists(s1))887 self.assertTrue(saver_module.checkpoint_exists(s2))888 self.assertTrue(saver_module.checkpoint_exists(s3))889 self.assertCheckpointState(890 model_checkpoint_path=s3,891 all_model_checkpoint_paths=[s2, s3],892 save_dir=save_dir)893 # Create a second helper, identical to the first.894 save2 = saver_module.Saver(saver_def=save.as_saver_def())895 save2.set_last_checkpoints(save.last_checkpoints)896 # Create a third helper, with the same configuration but no knowledge of897 # previous checkpoints.898 save3 = saver_module.Saver(saver_def=save.as_saver_def())899 # Exercise the first helper.900 # Adding s2 again (old s2 is removed first, then new s2 appended)901 s2 = save.save(sess, os.path.join(save_dir, "s2"))902 self.assertEqual([s3, s2], save.last_checkpoints)903 self.assertFalse(saver_module.checkpoint_exists(s1))904 self.assertFalse(905 saver_module.checkpoint_exists(save._MetaGraphFilename(s1)))906 self.assertTrue(saver_module.checkpoint_exists(s3))907 self.assertTrue(908 saver_module.checkpoint_exists(save._MetaGraphFilename(s3)))909 self.assertTrue(saver_module.checkpoint_exists(s2))910 self.assertTrue(911 saver_module.checkpoint_exists(save._MetaGraphFilename(s2)))912 self.assertCheckpointState(913 model_checkpoint_path=s2,914 all_model_checkpoint_paths=[s3, s2],915 save_dir=save_dir)916 # Adding s1 (s3 should now be deleted as oldest in list)917 s1 = save.save(sess, os.path.join(save_dir, "s1"))918 self.assertEqual([s2, s1], save.last_checkpoints)919 self.assertFalse(saver_module.checkpoint_exists(s3))920 self.assertFalse(921 saver_module.checkpoint_exists(save._MetaGraphFilename(s3)))922 self.assertTrue(saver_module.checkpoint_exists(s2))923 self.assertTrue(924 saver_module.checkpoint_exists(save._MetaGraphFilename(s2)))925 self.assertTrue(saver_module.checkpoint_exists(s1))926 self.assertTrue(927 saver_module.checkpoint_exists(save._MetaGraphFilename(s1)))928 self.assertCheckpointState(929 model_checkpoint_path=s1,930 all_model_checkpoint_paths=[s2, s1],931 save_dir=save_dir)932 # Exercise the second helper.933 # Adding s2 again (old s2 is removed first, then new s2 appended)934 s2 = save2.save(sess, os.path.join(save_dir, "s2"))935 self.assertEqual([s3, s2], save2.last_checkpoints)936 # Created by the first helper.937 self.assertTrue(saver_module.checkpoint_exists(s1))938 self.assertTrue(939 saver_module.checkpoint_exists(save._MetaGraphFilename(s1)))940 # Deleted by the first helper.941 self.assertFalse(saver_module.checkpoint_exists(s3))942 self.assertFalse(943 saver_module.checkpoint_exists(save._MetaGraphFilename(s3)))944 self.assertTrue(saver_module.checkpoint_exists(s2))945 self.assertTrue(946 saver_module.checkpoint_exists(save._MetaGraphFilename(s2)))947 self.assertCheckpointState(948 model_checkpoint_path=s2,949 all_model_checkpoint_paths=[s3, s2],950 save_dir=save_dir)951 # Adding s1 (s3 should now be deleted as oldest in list)952 s1 = save2.save(sess, os.path.join(save_dir, "s1"))953 self.assertEqual([s2, s1], save2.last_checkpoints)954 self.assertFalse(saver_module.checkpoint_exists(s3))955 self.assertFalse(956 saver_module.checkpoint_exists(save._MetaGraphFilename(s3)))957 self.assertTrue(saver_module.checkpoint_exists(s2))958 self.assertTrue(959 saver_module.checkpoint_exists(save._MetaGraphFilename(s2)))960 self.assertTrue(saver_module.checkpoint_exists(s1))961 self.assertTrue(962 saver_module.checkpoint_exists(save._MetaGraphFilename(s1)))963 self.assertCheckpointState(964 model_checkpoint_path=s1,965 all_model_checkpoint_paths=[s2, s1],966 save_dir=save_dir)967 # Exercise the third helper.968 # Adding s2 again (but helper is unaware of previous s2)969 s2 = save3.save(sess, os.path.join(save_dir, "s2"))970 self.assertEqual([s2], save3.last_checkpoints)971 # Created by the first helper.972 self.assertTrue(saver_module.checkpoint_exists(s1))973 self.assertTrue(974 saver_module.checkpoint_exists(save._MetaGraphFilename(s1)))975 # Deleted by the first helper.976 self.assertFalse(saver_module.checkpoint_exists(s3))977 self.assertFalse(978 saver_module.checkpoint_exists(save._MetaGraphFilename(s3)))979 self.assertTrue(saver_module.checkpoint_exists(s2))980 self.assertTrue(981 saver_module.checkpoint_exists(save._MetaGraphFilename(s2)))982 # Even though the file for s1 exists, this saver isn't aware of it, which983 # is why it doesn't end up in the checkpoint state.984 self.assertCheckpointState(985 model_checkpoint_path=s2,986 all_model_checkpoint_paths=[s2],987 save_dir=save_dir)988 # Adding s1 (s3 should not be deleted because helper is unaware of it)989 s1 = save3.save(sess, os.path.join(save_dir, "s1"))990 self.assertEqual([s2, s1], save3.last_checkpoints)991 self.assertFalse(saver_module.checkpoint_exists(s3))992 self.assertFalse(993 saver_module.checkpoint_exists(save._MetaGraphFilename(s3)))994 self.assertTrue(saver_module.checkpoint_exists(s2))995 self.assertTrue(996 saver_module.checkpoint_exists(save._MetaGraphFilename(s2)))997 self.assertTrue(saver_module.checkpoint_exists(s1))998 self.assertTrue(999 saver_module.checkpoint_exists(save._MetaGraphFilename(s1)))1000 self.assertCheckpointState(1001 model_checkpoint_path=s1,1002 all_model_checkpoint_paths=[s2, s1],1003 save_dir=save_dir)1004 def testSharded(self):1005 save_dir = self._get_test_dir("max_to_keep_sharded")1006 with session.Session(1007 target="",1008 config=config_pb2.ConfigProto(device_count={"CPU": 2})) as sess:1009 with sess.graph.device("/​cpu:0"):1010 v0 = variables.Variable(111, name="v0")1011 with sess.graph.device("/​cpu:1"):1012 v1 = variables.Variable(222, name="v1")1013 save = saver_module.Saver(1014 {1015 "v0": v0,1016 "v1": v11017 }, sharded=True, max_to_keep=2)1018 variables.global_variables_initializer().run()1019 self.assertEqual([], save.last_checkpoints)1020 s1 = save.save(sess, os.path.join(save_dir, "s1"))1021 self.assertEqual([s1], save.last_checkpoints)1022 if save._write_version is saver_pb2.SaverDef.V1:1023 self.assertEqual(2, len(gfile.Glob(s1)))1024 else:1025 self.assertEqual(4, len(gfile.Glob(s1 + "*")))1026 self.assertTrue(gfile.Exists(save._MetaGraphFilename(s1)))1027 s2 = save.save(sess, os.path.join(save_dir, "s2"))1028 self.assertEqual([s1, s2], save.last_checkpoints)1029 if save._write_version is saver_pb2.SaverDef.V1:1030 self.assertEqual(2, len(gfile.Glob(s1)))1031 else:1032 self.assertEqual(4, len(gfile.Glob(s1 + "*")))1033 self.assertTrue(gfile.Exists(save._MetaGraphFilename(s1)))1034 if save._write_version is saver_pb2.SaverDef.V1:1035 self.assertEqual(2, len(gfile.Glob(s2)))1036 else:1037 self.assertEqual(4, len(gfile.Glob(s2 + "*")))1038 self.assertTrue(gfile.Exists(save._MetaGraphFilename(s2)))1039 s3 = save.save(sess, os.path.join(save_dir, "s3"))1040 self.assertEqual([s2, s3], save.last_checkpoints)1041 self.assertEqual(0, len(gfile.Glob(s1 + "*")))1042 self.assertFalse(gfile.Exists(save._MetaGraphFilename(s1)))1043 if save._write_version is saver_pb2.SaverDef.V1:1044 self.assertEqual(2, len(gfile.Glob(s2)))1045 else:1046 self.assertEqual(4, len(gfile.Glob(s2 + "*")))1047 self.assertTrue(gfile.Exists(save._MetaGraphFilename(s2)))1048 if save._write_version is saver_pb2.SaverDef.V1:1049 self.assertEqual(2, len(gfile.Glob(s3)))1050 else:1051 self.assertEqual(4, len(gfile.Glob(s3 + "*")))1052 self.assertTrue(gfile.Exists(save._MetaGraphFilename(s3)))1053 def testNoMaxToKeep(self):1054 save_dir = self._get_test_dir("no_max_to_keep")1055 save_dir2 = self._get_test_dir("max_to_keep_0")1056 with self.test_session() as sess:1057 v = variables.Variable(10.0, name="v")1058 variables.global_variables_initializer().run()1059 # Test max_to_keep being None.1060 save = saver_module.Saver({"v": v}, max_to_keep=None)1061 self.assertEqual([], save.last_checkpoints)1062 s1 = save.save(sess, os.path.join(save_dir, "s1"))1063 self.assertEqual([], save.last_checkpoints)1064 self.assertTrue(saver_module.checkpoint_exists(s1))1065 s2 = save.save(sess, os.path.join(save_dir, "s2"))1066 self.assertEqual([], save.last_checkpoints)1067 self.assertTrue(saver_module.checkpoint_exists(s2))1068 # Test max_to_keep being 0.1069 save2 = saver_module.Saver({"v": v}, max_to_keep=0)1070 self.assertEqual([], save2.last_checkpoints)1071 s1 = save2.save(sess, os.path.join(save_dir2, "s1"))1072 self.assertEqual([], save2.last_checkpoints)1073 self.assertTrue(saver_module.checkpoint_exists(s1))1074 s2 = save2.save(sess, os.path.join(save_dir2, "s2"))1075 self.assertEqual([], save2.last_checkpoints)1076 self.assertTrue(saver_module.checkpoint_exists(s2))1077 def testNoMetaGraph(self):1078 save_dir = self._get_test_dir("no_meta_graph")1079 with self.test_session() as sess:1080 v = variables.Variable(10.0, name="v")1081 save = saver_module.Saver({"v": v})1082 variables.global_variables_initializer().run()1083 s1 = save.save(sess, os.path.join(save_dir, "s1"), write_meta_graph=False)1084 self.assertTrue(saver_module.checkpoint_exists(s1))1085 self.assertFalse(gfile.Exists(save._MetaGraphFilename(s1)))1086class KeepCheckpointEveryNHoursTest(test.TestCase):1087 def _get_test_dir(self, dirname):1088 test_dir = os.path.join(self.get_temp_dir(), dirname)1089 gfile.MakeDirs(test_dir)1090 return test_dir1091 @test.mock.patch.object(saver_module, "time")1092 def testNonSharded(self, mock_time):1093 save_dir = self._get_test_dir("keep_checkpoint_every_n_hours")1094 with self.test_session() as sess:1095 v = variables.Variable([10.0], name="v")1096 # Run the initializer NOW to avoid the 0.5s overhead of the first Run()1097 # call, which throws the test timing off in fastbuild mode.1098 variables.global_variables_initializer().run()1099 # Create a saver that will keep the last 2 checkpoints plus one every 0.71100 # seconds.1101 start_time = time.time()1102 mock_time.time.return_value = start_time1103 save = saver_module.Saver(1104 {1105 "v": v1106 }, max_to_keep=2, keep_checkpoint_every_n_hours=0.7 /​ 3600)1107 self.assertEqual([], save.last_checkpoints)1108 # Wait till 1 seconds have elapsed so s1 will be old enough to keep.1109 # sleep may return early, don't trust it.1110 mock_time.time.return_value = start_time + 1.01111 s1 = save.save(sess, os.path.join(save_dir, "s1"))1112 self.assertEqual([s1], save.last_checkpoints)1113 s2 = save.save(sess, os.path.join(save_dir, "s2"))1114 self.assertEqual([s1, s2], save.last_checkpoints)1115 # We now have 2 'last_checkpoints': [s1, s2]. The next call to Save(),1116 # would normally delete s1, because max_to_keep is 2. However, s1 is1117 # older than 0.7s so we must keep it.1118 s3 = save.save(sess, os.path.join(save_dir, "s3"))1119 self.assertEqual([s2, s3], save.last_checkpoints)1120 # s1 should still be here, we are Not checking now to reduce time1121 # variance in the test.1122 # We now have 2 'last_checkpoints': [s2, s3], and s1 on disk. The next1123 # call to Save(), will delete s2, because max_to_keep is 2, and because1124 # we already kept the old s1. s2 is very close in time to s1 so it gets1125 # deleted.1126 s4 = save.save(sess, os.path.join(save_dir, "s4"))1127 self.assertEqual([s3, s4], save.last_checkpoints)1128 # Check that s1 is still here, but s2 is gone.1129 self.assertTrue(saver_module.checkpoint_exists(s1))1130 self.assertFalse(saver_module.checkpoint_exists(s2))1131 self.assertTrue(saver_module.checkpoint_exists(s3))1132 self.assertTrue(saver_module.checkpoint_exists(s4))1133class SaveRestoreWithVariableNameMap(test.TestCase):1134 def _testNonReshape(self, variable_op):1135 save_path = os.path.join(self.get_temp_dir(), "non_reshape")1136 with self.test_session(graph=ops_lib.Graph()) as sess:1137 # Build a graph with 2 parameter nodes, and Save and1138 # Restore nodes for them.1139 v0 = variable_op(10.0, name="v0")1140 v1 = variable_op(20.0, name="v1")1141 save = saver_module.Saver({"save_prefix/​v0": v0, "save_prefix/​v1": v1})1142 self.evaluate(variables.global_variables_initializer())1143 # Check that the parameter nodes have been initialized.1144 self.assertEqual(10.0, self.evaluate(v0))1145 self.assertEqual(20.0, self.evaluate(v1))1146 # Save the initialized values in the file at "save_path"1147 # Use a variable name map to set the saved tensor names1148 val = save.save(sess, save_path)1149 self.assertTrue(isinstance(val, six.string_types))1150 self.assertEqual(save_path, val)1151 # Verify that the original names are not in the Saved file1152 save = saver_module.Saver({"v0": v0, "v1": v1})1153 with self.assertRaisesOpError("not found in checkpoint"):1154 save.restore(sess, save_path)1155 # Verify that the mapped names are present in the Saved file and can be1156 # Restored using remapped names.1157 with self.test_session(graph=ops_lib.Graph()) as sess:1158 v0 = variable_op(-1.0, name="v0")1159 v1 = variable_op(-1.0, name="v1")1160 if context.in_graph_mode():1161 with self.assertRaisesOpError("uninitialized"):1162 self.evaluate(v0)1163 with self.assertRaisesOpError("uninitialized"):1164 self.evaluate(v1)1165 save = saver_module.Saver({"save_prefix/​v0": v0, "save_prefix/​v1": v1})1166 save.restore(sess, save_path)1167 # Check that the parameter nodes have been restored.1168 if context.in_graph_mode():1169 self.assertEqual(10.0, self.evaluate(v0))1170 self.assertEqual(20.0, self.evaluate(v1))1171 # Add a prefix to the node names in the current graph and Restore using1172 # remapped names.1173 with self.test_session(graph=ops_lib.Graph()) as sess:1174 v0 = variable_op(-1.0, name="restore_prefix/​v0")1175 v1 = variable_op(-1.0, name="restore_prefix/​v1")1176 if context.in_graph_mode():1177 with self.assertRaisesOpError("uninitialized"):1178 self.evaluate(v0)1179 with self.assertRaisesOpError("uninitialized"):1180 self.evaluate(v1)1181 # Restore the saved values in the parameter nodes.1182 save = saver_module.Saver({"save_prefix/​v0": v0, "save_prefix/​v1": v1})1183 save.restore(sess, save_path)1184 # Check that the parameter nodes have been restored.1185 self.assertEqual(10.0, self.evaluate(v0))1186 self.assertEqual(20.0, self.evaluate(v1))1187 @test_util.run_in_graph_and_eager_modes()1188 def testNonReshapeResourceVariable(self):1189 self._testNonReshape(resource_variable_ops.ResourceVariable)1190 def testNonReshapeVariable(self):1191 self._testNonReshape(variables.Variable)1192class LatestCheckpointWithRelativePaths(test.TestCase):1193 @staticmethod1194 @contextlib.contextmanager1195 def tempWorkingDir(temppath):1196 cwd = os.getcwd()1197 os.chdir(temppath)1198 try:1199 yield1200 finally:1201 os.chdir(cwd)1202 @staticmethod1203 @contextlib.contextmanager1204 def tempDir():1205 tempdir = tempfile.mkdtemp()1206 try:1207 yield tempdir1208 finally:1209 shutil.rmtree(tempdir)1210 def testNameCollision(self):1211 # Make sure we have a clean directory to work in.1212 with self.tempDir() as tempdir:1213 # Jump to that directory until this test is done.1214 with self.tempWorkingDir(tempdir):1215 # Save training snapshots to a relative path.1216 traindir = "train/​"1217 os.mkdir(traindir)1218 # Collides with the default name of the checkpoint state file.1219 filepath = os.path.join(traindir, "checkpoint")1220 with self.test_session() as sess:1221 unused_a = variables.Variable(0.0) # So that Saver saves something.1222 variables.global_variables_initializer().run()1223 # Should fail.1224 saver = saver_module.Saver(sharded=False)1225 with self.assertRaisesRegexp(ValueError, "collides with"):1226 saver.save(sess, filepath)1227 # Succeeds: the file will be named "checkpoint-<step>".1228 saver.save(sess, filepath, global_step=1)1229 self.assertIsNotNone(saver_module.latest_checkpoint(traindir))1230 # Succeeds: the file will be named "checkpoint-<i>-of-<n>".1231 saver = saver_module.Saver(sharded=True)1232 saver.save(sess, filepath)1233 self.assertIsNotNone(saver_module.latest_checkpoint(traindir))1234 # Succeeds: the file will be named "checkpoint-<step>-<i>-of-<n>".1235 saver = saver_module.Saver(sharded=True)1236 saver.save(sess, filepath, global_step=1)1237 self.assertIsNotNone(saver_module.latest_checkpoint(traindir))1238 def testRelativePath(self):1239 # Make sure we have a clean directory to work in.1240 with self.tempDir() as tempdir:1241 # Jump to that directory until this test is done.1242 with self.tempWorkingDir(tempdir):1243 # Save training snapshots to a relative path.1244 traindir = "train/​"1245 os.mkdir(traindir)1246 filename = "snapshot"1247 filepath = os.path.join(traindir, filename)1248 with self.test_session() as sess:1249 # Build a simple graph.1250 v0 = variables.Variable(0.0)1251 inc = v0.assign_add(1.0)1252 save = saver_module.Saver({"v0": v0})1253 # Record a short training history.1254 variables.global_variables_initializer().run()1255 save.save(sess, filepath, global_step=0)1256 inc.eval()1257 save.save(sess, filepath, global_step=1)1258 inc.eval()1259 save.save(sess, filepath, global_step=2)1260 with self.test_session() as sess:1261 # Build a new graph with different initialization.1262 v0 = variables.Variable(-1.0)1263 # Create a new saver.1264 save = saver_module.Saver({"v0": v0})1265 variables.global_variables_initializer().run()1266 # Get the most recent checkpoint name from the training history file.1267 name = saver_module.latest_checkpoint(traindir)1268 self.assertIsNotNone(name)1269 # Restore "v0" from that checkpoint.1270 save.restore(sess, name)1271 self.assertEqual(v0.eval(), 2.0)1272class CheckpointStateTest(test.TestCase):1273 def _get_test_dir(self, dirname):1274 test_dir = os.path.join(self.get_temp_dir(), dirname)1275 gfile.MakeDirs(test_dir)1276 return test_dir1277 def testAbsPath(self):1278 save_dir = self._get_test_dir("abs_paths")1279 abs_path = os.path.join(save_dir, "model-0")1280 ckpt = saver_module.generate_checkpoint_state_proto(save_dir, abs_path)1281 self.assertEqual(ckpt.model_checkpoint_path, abs_path)1282 self.assertTrue(os.path.isabs(ckpt.model_checkpoint_path))1283 self.assertEqual(len(ckpt.all_model_checkpoint_paths), 1)1284 self.assertEqual(ckpt.all_model_checkpoint_paths[-1], abs_path)1285 def testRelPath(self):1286 train_dir = "train"1287 model = os.path.join(train_dir, "model-0")1288 # model_checkpoint_path should have no "train" directory part.1289 new_rel_path = "model-0"1290 ckpt = saver_module.generate_checkpoint_state_proto(train_dir, model)1291 self.assertEqual(ckpt.model_checkpoint_path, new_rel_path)1292 self.assertEqual(len(ckpt.all_model_checkpoint_paths), 1)1293 self.assertEqual(ckpt.all_model_checkpoint_paths[-1], new_rel_path)1294 def testAllModelCheckpointPaths(self):1295 save_dir = self._get_test_dir("all_models_test")1296 abs_path = os.path.join(save_dir, "model-0")1297 for paths in [None, [], ["model-2"]]:1298 ckpt = saver_module.generate_checkpoint_state_proto(1299 save_dir, abs_path, all_model_checkpoint_paths=paths)1300 self.assertEqual(ckpt.model_checkpoint_path, abs_path)1301 self.assertTrue(os.path.isabs(ckpt.model_checkpoint_path))1302 self.assertEqual(1303 len(ckpt.all_model_checkpoint_paths), len(paths) if paths else 1)1304 self.assertEqual(ckpt.all_model_checkpoint_paths[-1], abs_path)1305 def testUpdateCheckpointState(self):1306 save_dir = self._get_test_dir("update_checkpoint_state")1307 os.chdir(save_dir)1308 # Make a temporary train directory.1309 train_dir = "train"1310 os.mkdir(train_dir)1311 abs_path = os.path.join(save_dir, "model-0")1312 rel_path = os.path.join("train", "model-2")1313 saver_module.update_checkpoint_state(1314 train_dir, rel_path, all_model_checkpoint_paths=[abs_path, rel_path])1315 ckpt = saver_module.get_checkpoint_state(train_dir)1316 self.assertEqual(ckpt.model_checkpoint_path, rel_path)1317 self.assertEqual(len(ckpt.all_model_checkpoint_paths), 2)1318 self.assertEqual(ckpt.all_model_checkpoint_paths[-1], rel_path)1319 self.assertEqual(ckpt.all_model_checkpoint_paths[0], abs_path)1320 def testUpdateCheckpointStateSaveRelativePaths(self):1321 save_dir = self._get_test_dir("update_checkpoint_state")1322 os.chdir(save_dir)1323 abs_path2 = os.path.join(save_dir, "model-2")1324 rel_path2 = "model-2"1325 abs_path0 = os.path.join(save_dir, "model-0")1326 rel_path0 = "model-0"1327 saver_module._update_checkpoint_state( # pylint: disable=protected-access1328 save_dir=save_dir,1329 model_checkpoint_path=abs_path2,1330 all_model_checkpoint_paths=[rel_path0, abs_path2],1331 save_relative_paths=True)1332 # File should contain relative paths.1333 file_content = file_io.read_file_to_string(1334 os.path.join(save_dir, "checkpoint"))1335 ckpt = CheckpointState()1336 text_format.Merge(file_content, ckpt)1337 self.assertEqual(ckpt.model_checkpoint_path, rel_path2)1338 self.assertEqual(len(ckpt.all_model_checkpoint_paths), 2)1339 self.assertEqual(ckpt.all_model_checkpoint_paths[-1], rel_path2)1340 self.assertEqual(ckpt.all_model_checkpoint_paths[0], rel_path0)1341 # get_checkpoint_state should return absolute paths.1342 ckpt = saver_module.get_checkpoint_state(save_dir)1343 self.assertEqual(ckpt.model_checkpoint_path, abs_path2)1344 self.assertEqual(len(ckpt.all_model_checkpoint_paths), 2)1345 self.assertEqual(ckpt.all_model_checkpoint_paths[-1], abs_path2)1346 self.assertEqual(ckpt.all_model_checkpoint_paths[0], abs_path0)1347 def testCheckPointStateFailsWhenIncomplete(self):1348 save_dir = self._get_test_dir("checkpoint_state_fails_when_incomplete")1349 os.chdir(save_dir)1350 ckpt_path = os.path.join(save_dir, "checkpoint")1351 ckpt_file = open(ckpt_path, "w")1352 ckpt_file.write("")1353 ckpt_file.close()1354 with self.assertRaises(ValueError):1355 saver_module.get_checkpoint_state(save_dir)1356 def testCheckPointCompletesRelativePaths(self):1357 save_dir = self._get_test_dir("checkpoint_completes_relative_paths")1358 os.chdir(save_dir)1359 ckpt_path = os.path.join(save_dir, "checkpoint")1360 ckpt_file = open(ckpt_path, "w")1361 ckpt_file.write("""1362 model_checkpoint_path: "./​model.ckpt-687529"1363 all_model_checkpoint_paths: "./​model.ckpt-687500"1364 all_model_checkpoint_paths: "./​model.ckpt-687529"1365 """)1366 ckpt_file.close()1367 ckpt = saver_module.get_checkpoint_state(save_dir)1368 self.assertEqual(ckpt.model_checkpoint_path,1369 os.path.join(save_dir, "./​model.ckpt-687529"))1370 self.assertEqual(ckpt.all_model_checkpoint_paths[0],1371 os.path.join(save_dir, "./​model.ckpt-687500"))1372 self.assertEqual(ckpt.all_model_checkpoint_paths[1],1373 os.path.join(save_dir, "./​model.ckpt-687529"))1374class MetaGraphTest(test.TestCase):1375 def _get_test_dir(self, dirname):1376 test_dir = os.path.join(self.get_temp_dir(), dirname)1377 gfile.MakeDirs(test_dir)1378 return test_dir1379 def testAddCollectionDef(self):1380 test_dir = self._get_test_dir("good_collection")1381 filename = os.path.join(test_dir, "metafile")1382 with self.test_session():1383 # Creates a graph.1384 v0 = variables.Variable(1.0, name="v0")1385 control_flow_ops.cond(1386 math_ops.less(v0, 10), lambda: math_ops.add(v0, 1),1387 lambda: math_ops.subtract(v0, 1))1388 control_flow_ops.while_loop(lambda i: math_ops.less(i, 10),1389 lambda i: math_ops.add(i, 1), [v0])1390 var = variables.Variable(constant_op.constant(0, dtype=dtypes.int64))1391 count_up_to = var.count_up_to(3)1392 input_queue = data_flow_ops.FIFOQueue(1393 30, dtypes.float32, shared_name="collection_queue")1394 qr = queue_runner_impl.QueueRunner(input_queue, [count_up_to])1395 variables.global_variables_initializer()1396 # Creates a saver.1397 save = saver_module.Saver({"v0": v0})1398 # Adds a set of collections.1399 ops_lib.add_to_collection("int_collection", 3)1400 ops_lib.add_to_collection("float_collection", 3.5)1401 ops_lib.add_to_collection("string_collection", "hello")1402 ops_lib.add_to_collection("variable_collection", v0)1403 # Add QueueRunners.1404 queue_runner_impl.add_queue_runner(qr)1405 # Adds user_defined proto in three formats: string, bytes and Any.1406 queue_runner = queue_runner_pb2.QueueRunnerDef(queue_name="test_queue")1407 ops_lib.add_to_collection("user_defined_string_collection",1408 str(queue_runner))1409 ops_lib.add_to_collection("user_defined_bytes_collection",1410 queue_runner.SerializeToString())1411 any_buf = Any()1412 any_buf.Pack(queue_runner)1413 ops_lib.add_to_collection("user_defined_any_collection", any_buf)1414 # Generates MetaGraphDef.1415 meta_graph_def = save.export_meta_graph(filename)1416 self.assertTrue(meta_graph_def.HasField("saver_def"))1417 self.assertTrue(meta_graph_def.HasField("graph_def"))1418 self.assertTrue(meta_graph_def.HasField("meta_info_def"))1419 self.assertNotEqual(meta_graph_def.meta_info_def.tensorflow_version, "")1420 self.assertNotEqual(meta_graph_def.meta_info_def.tensorflow_git_version,1421 "")1422 collection_def = meta_graph_def.collection_def1423 self.assertEqual(len(collection_def), 12)1424 with ops_lib.Graph().as_default():1425 # Restores from MetaGraphDef.1426 new_saver = saver_module.import_meta_graph(filename)1427 # Generates a new MetaGraphDef.1428 new_meta_graph_def = new_saver.export_meta_graph()1429 # It should be the same as the original.1430 test_util.assert_meta_graph_protos_equal(1431 self, meta_graph_def, new_meta_graph_def)1432 def testAddCollectionDefFails(self):1433 with self.test_session():1434 # Creates a graph.1435 v0 = variables.Variable(10.0, name="v0")1436 # Creates a saver.1437 save = saver_module.Saver({"v0": v0})1438 # Generates MetaGraphDef.1439 meta_graph_def = meta_graph_pb2.MetaGraphDef()1440 # Verifies that collection with unsupported key will not be added.1441 ops_lib.add_to_collection(save, 3)1442 save._add_collection_def(meta_graph_def, save)1443 self.assertEqual(len(meta_graph_def.collection_def), 0)1444 # Verifies that collection where item type does not match expected1445 # type will not be added.1446 ops_lib.add_to_collection("int_collection", 3)1447 ops_lib.add_to_collection("int_collection", 3.5)1448 save._add_collection_def(meta_graph_def, "int_collection")1449 self.assertEqual(len(meta_graph_def.collection_def), 0)1450 def _testMultiSaverCollectionSave(self, test_dir):1451 filename = os.path.join(test_dir, "metafile")1452 saver0_ckpt = os.path.join(test_dir, "saver0.ckpt")1453 saver1_ckpt = os.path.join(test_dir, "saver1.ckpt")1454 with self.test_session(graph=ops_lib.Graph()) as sess:1455 # Creates a graph.1456 v0 = variables.Variable([[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]], name="v0")1457 v1 = variables.Variable(11.0, name="v1")1458 # Creates 2 savers.1459 saver0 = saver_module.Saver({"v0": v0}, name="saver0")1460 saver1 = saver_module.Saver({"v1": v1}, name="saver1")1461 ops_lib.add_to_collection("savers", saver0)1462 ops_lib.add_to_collection("savers", saver1)1463 variables.global_variables_initializer().run()1464 # Saves to different checkpoints.1465 saver0.save(sess, saver0_ckpt)1466 saver1.save(sess, saver1_ckpt)1467 # Generates MetaGraphDef.1468 meta_graph_def = saver_module.export_meta_graph(filename)1469 meta_graph_def0 = saver0.export_meta_graph()1470 meta_graph_def1 = saver1.export_meta_graph()1471 # Verifies that there is no saver_def in meta_graph_def.1472 self.assertFalse(meta_graph_def.HasField("saver_def"))1473 # Verifies that there is saver_def in meta_graph_def0 and 1.1474 self.assertTrue(meta_graph_def0.HasField("saver_def"))1475 self.assertTrue(meta_graph_def1.HasField("saver_def"))1476 # Verifies SAVERS is saved as bytes_list for meta_graph_def.1477 collection_def = meta_graph_def.collection_def["savers"]1478 kind = collection_def.WhichOneof("kind")1479 self.assertEqual(kind, "bytes_list")1480 # Verifies that there are 2 entries in SAVERS collection.1481 savers = getattr(collection_def, kind)1482 self.assertEqual(2, len(savers.value))1483 # Verifies SAVERS collection is saved as bytes_list for meta_graph_def0.1484 collection_def = meta_graph_def0.collection_def["savers"]1485 kind = collection_def.WhichOneof("kind")1486 self.assertEqual(kind, "bytes_list")1487 # Verifies that there are 2 entries in SAVERS collection.1488 savers = getattr(collection_def, kind)1489 self.assertEqual(2, len(savers.value))1490 def _testMultiSaverCollectionRestore(self, test_dir):1491 filename = os.path.join(test_dir, "metafile")1492 saver0_ckpt = os.path.join(test_dir, "saver0.ckpt")1493 saver1_ckpt = os.path.join(test_dir, "saver1.ckpt")1494 with self.test_session(graph=ops_lib.Graph()) as sess:1495 # Imports from meta_graph.1496 saver_module.import_meta_graph(filename)1497 # Retrieves SAVERS collection. Verifies there are 2 entries.1498 savers = ops_lib.get_collection("savers")1499 self.assertEqual(2, len(savers))1500 # Retrieves saver0. Verifies that new_saver0 can restore v0, but not v1.1501 new_saver0 = savers[0]1502 new_saver0.restore(sess, saver0_ckpt)1503 v0 = sess.graph.get_tensor_by_name("v0:0")1504 v1 = sess.graph.get_tensor_by_name("v1:0")1505 self.assertAllEqual([[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]], v0.eval())1506 self.assertEqual([3, 2], v0.get_shape())1507 self.assertEqual([], v1.get_shape())1508 with self.assertRaisesWithPredicateMatch(1509 errors_impl.OpError, lambda e: "uninitialized value v1" in e.message):1510 sess.run(v1)1511 # Retrieves saver1. Verifies that new_saver1 can restore v1.1512 new_saver1 = savers[1]1513 new_saver1.restore(sess, saver1_ckpt)1514 v1 = sess.graph.get_tensor_by_name("v1:0")1515 self.assertEqual(11.0, v1.eval())1516 def testMultiSaverCollection(self):1517 test_dir = self._get_test_dir("saver_collection")1518 self._testMultiSaverCollectionSave(test_dir)1519 self._testMultiSaverCollectionRestore(test_dir)1520 def testClearExtraneousSavers(self):1521 test_dir = self._get_test_dir("clear_extraneous_savers")1522 filename = os.path.join(test_dir, "metafile")1523 saver0_ckpt = os.path.join(test_dir, "saver0.ckpt")1524 saver1_ckpt = os.path.join(test_dir, "saver1.ckpt")1525 with self.test_session(graph=ops_lib.Graph()) as sess:1526 # Creates a graph.1527 v0 = variables.Variable([[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]], name="v0")1528 v1 = variables.Variable(11.0, name="v1")1529 # Creates 2 savers.1530 saver0 = saver_module.Saver({"v0": v0}, name="saver0")1531 saver1 = saver_module.Saver({"v1": v1}, name="saver1")1532 ops_lib.add_to_collection("savers", saver0)1533 ops_lib.add_to_collection("savers", saver1)1534 variables.global_variables_initializer().run()1535 # Saves to different checkpoints.1536 saver0.save(sess, saver0_ckpt)1537 saver1.save(sess, saver1_ckpt)1538 # Generates MetaGraphDef.1539 meta_graph_def = saver_module.export_meta_graph(filename)1540 meta_graph_def0 = saver0.export_meta_graph()1541 meta_graph_def1 = saver1.export_meta_graph(clear_extraneous_savers=True)1542 # Verifies that there is no saver_def in meta_graph_def.1543 self.assertFalse(meta_graph_def.HasField("saver_def"))1544 # Verifies that there is saver_def in meta_graph_def0 and 1.1545 self.assertTrue(meta_graph_def0.HasField("saver_def"))1546 self.assertTrue(meta_graph_def1.HasField("saver_def"))1547 # Verifies SAVERS is saved as bytes_list for meta_graph_def.1548 collection_def = meta_graph_def.collection_def["savers"]1549 kind = collection_def.WhichOneof("kind")1550 self.assertEqual(kind, "bytes_list")1551 # Verifies that there are 2 entries in SAVERS collection.1552 savers = getattr(collection_def, kind)1553 self.assertEqual(2, len(savers.value))1554 # Verifies SAVERS collection is saved as bytes_list for meta_graph_def1.1555 collection_def = meta_graph_def1.collection_def["savers"]1556 kind = collection_def.WhichOneof("kind")1557 self.assertEqual(kind, "bytes_list")1558 # Verifies that there is 1 entry in SAVERS collection.1559 savers = getattr(collection_def, kind)1560 self.assertEqual(1, len(savers.value))1561 # Verifies that saver0 graph nodes are omitted from the saver1 export1562 self.assertEqual(29, len(meta_graph_def0.graph_def.node))1563 self.assertEqual(19, len(meta_graph_def1.graph_def.node))1564 def testBinaryAndTextFormat(self):1565 test_dir = self._get_test_dir("binary_and_text")1566 filename = os.path.join(test_dir, "metafile")1567 with self.test_session(graph=ops_lib.Graph()):1568 # Creates a graph.1569 variables.Variable(10.0, name="v0")1570 # Exports the graph as binary format.1571 saver_module.export_meta_graph(filename, as_text=False)1572 with self.test_session(graph=ops_lib.Graph()):1573 # Imports the binary format graph.1574 saver = saver_module.import_meta_graph(filename)1575 self.assertIsNotNone(saver)1576 # Exports the graph as text format.1577 saver.export_meta_graph(filename, as_text=True)1578 with self.test_session(graph=ops_lib.Graph()):1579 # Imports the text format graph.1580 saver_module.import_meta_graph(filename)1581 # Writes wrong contents to the file.1582 graph_io.write_graph(saver.as_saver_def(),1583 os.path.dirname(filename),1584 os.path.basename(filename))1585 with self.test_session(graph=ops_lib.Graph()):1586 # Import should fail.1587 with self.assertRaisesWithPredicateMatch(IOError,1588 lambda e: "Cannot parse file"):1589 saver_module.import_meta_graph(filename)1590 # Deletes the file1591 gfile.Remove(filename)1592 with self.assertRaisesWithPredicateMatch(IOError,1593 lambda e: "does not exist"):1594 saver_module.import_meta_graph(filename)1595 def testSliceVariable(self):1596 test_dir = self._get_test_dir("slice_saver")1597 filename = os.path.join(test_dir, "metafile")1598 with self.test_session():1599 v1 = variables.Variable([20.0], name="v1")1600 v2 = variables.Variable([20.0], name="v2")1601 v2._set_save_slice_info(1602 variables.Variable.SaveSliceInfo("v1", [1], [0], [1]))1603 # The names are different and will work.1604 slice_saver = saver_module.Saver({"first": v1, "second": v2})1605 variables.global_variables_initializer().run()1606 # Exports to meta_graph1607 meta_graph_def = slice_saver.export_meta_graph(filename)1608 with ops_lib.Graph().as_default():1609 # Restores from MetaGraphDef.1610 new_saver = saver_module.import_meta_graph(filename)1611 self.assertIsNotNone(new_saver)1612 # Generates a new MetaGraphDef.1613 new_meta_graph_def = new_saver.export_meta_graph()1614 # It should be the same as the original.1615 self.assertProtoEquals(meta_graph_def, new_meta_graph_def)1616 def _testGraphExtensionSave(self, test_dir):1617 filename = os.path.join(test_dir, "metafile")1618 saver0_ckpt = os.path.join(test_dir, "saver0.ckpt")1619 # Creates an inference graph.1620 # Hidden 11621 images = constant_op.constant(1.2, dtypes.float32, shape=[100, 28])1622 with ops_lib.name_scope("hidden1"):1623 weights = variables.Variable(1624 random_ops.truncated_normal(1625 [28, 128], stddev=1.0 /​ math.sqrt(float(28))),1626 name="weights")1627 # The use of control_flow_ops.cond here is purely for adding test coverage1628 # the save and restore of control flow context (which doesn't make any1629 # sense here from a machine learning perspective). The typical biases is1630 # a simple Variable without the conditions.1631 biases = variables.Variable(1632 control_flow_ops.cond(1633 math_ops.less(random.random(), 0.5),1634 lambda: array_ops.ones([128]), lambda: array_ops.zeros([128])),1635 name="biases")1636 hidden1 = nn_ops.relu(math_ops.matmul(images, weights) + biases)1637 # Hidden 21638 with ops_lib.name_scope("hidden2"):1639 weights = variables.Variable(1640 random_ops.truncated_normal(1641 [128, 32], stddev=1.0 /​ math.sqrt(float(128))),1642 name="weights")1643 # The use of control_flow_ops.while_loop here is purely for adding test1644 # coverage the save and restore of control flow context (which doesn't1645 # make any sense here from a machine learning perspective). The typical1646 # biases is a simple Variable without the conditions.1647 def loop_cond(it, _):1648 return it < 21649 def loop_body(it, biases):1650 biases += constant_op.constant(0.1, shape=[32])1651 return it + 1, biases1652 _, biases = control_flow_ops.while_loop(1653 loop_cond, loop_body,1654 [constant_op.constant(0), variables.Variable(array_ops.zeros([32]))])1655 hidden2 = nn_ops.relu(math_ops.matmul(hidden1, weights) + biases)1656 # Linear1657 with ops_lib.name_scope("softmax_linear"):1658 weights = variables.Variable(1659 random_ops.truncated_normal(1660 [32, 10], stddev=1.0 /​ math.sqrt(float(32))),1661 name="weights")1662 biases = variables.Variable(array_ops.zeros([10]), name="biases")1663 logits = math_ops.matmul(hidden2, weights) + biases1664 ops_lib.add_to_collection("logits", logits)1665 init_all_op = variables.global_variables_initializer()1666 with self.test_session() as sess:1667 # Initializes all the variables.1668 sess.run(init_all_op)1669 # Runs to logit.1670 sess.run(logits)1671 # Creates a saver.1672 saver0 = saver_module.Saver()1673 saver0.save(sess, saver0_ckpt)1674 # Generates MetaGraphDef.1675 saver0.export_meta_graph(filename)1676 def _testGraphExtensionRestore(self, test_dir):1677 filename = os.path.join(test_dir, "metafile")1678 train_filename = os.path.join(test_dir, "train_metafile")1679 saver0_ckpt = os.path.join(test_dir, "saver0.ckpt")1680 with self.test_session(graph=ops_lib.Graph()) as sess:1681 # Restores from MetaGraphDef.1682 new_saver = saver_module.import_meta_graph(filename)1683 # Generates a new MetaGraphDef.1684 new_saver.export_meta_graph()1685 # Restores from checkpoint.1686 new_saver.restore(sess, saver0_ckpt)1687 # Adds loss and train.1688 labels = constant_op.constant(0, dtypes.int32, shape=[100], name="labels")1689 batch_size = array_ops.size(labels)1690 labels = array_ops.expand_dims(labels, 1)1691 indices = array_ops.expand_dims(math_ops.range(0, batch_size), 1)1692 concated = array_ops.concat([indices, labels], 1)1693 onehot_labels = sparse_ops.sparse_to_dense(1694 concated, array_ops.stack([batch_size, 10]), 1.0, 0.0)1695 logits = ops_lib.get_collection("logits")[0]1696 cross_entropy = nn_ops.softmax_cross_entropy_with_logits(1697 labels=onehot_labels, logits=logits, name="xentropy")1698 loss = math_ops.reduce_mean(cross_entropy, name="xentropy_mean")1699 summary.scalar("loss", loss)1700 # Creates the gradient descent optimizer with the given learning rate.1701 optimizer = gradient_descent.GradientDescentOptimizer(0.01)1702 # Runs train_op.1703 train_op = optimizer.minimize(loss)1704 ops_lib.add_to_collection("train_op", train_op)1705 # Runs train_op.1706 sess.run(train_op)1707 # Generates MetaGraphDef.1708 saver_module.export_meta_graph(train_filename)1709 def _testRestoreFromTrainGraphWithControlContext(self, test_dir):1710 train_filename = os.path.join(test_dir, "train_metafile")1711 saver0_ckpt = os.path.join(test_dir, "saver0.ckpt")1712 with self.test_session(graph=ops_lib.Graph()) as sess:1713 # Restores from MetaGraphDef.1714 new_saver = saver_module.import_meta_graph(train_filename)1715 # Restores from checkpoint.1716 new_saver.restore(sess, saver0_ckpt)1717 train_op = ops_lib.get_collection("train_op")[0]1718 sess.run(train_op)1719 def testGraphExtension(self):1720 test_dir = self._get_test_dir("graph_extension")1721 self._testGraphExtensionSave(test_dir)1722 self._testGraphExtensionRestore(test_dir)1723 self._testRestoreFromTrainGraphWithControlContext(test_dir)1724 def testStrippedOpListDef(self):1725 with self.test_session():1726 # Creates a graph.1727 v0 = variables.Variable(0.0)1728 var = variables.Variable(10.0)1729 math_ops.add(v0, var)1730 @function.Defun(dtypes.float32)1731 def minus_one(x):1732 return x - 11733 minus_one(array_ops.identity(v0))1734 save = saver_module.Saver({"v0": v0})1735 variables.global_variables_initializer()1736 # Generates MetaGraphDef.1737 meta_graph_def = save.export_meta_graph()1738 ops = [o.name for o in meta_graph_def.meta_info_def.stripped_op_list.op]1739 if save._write_version is saver_pb2.SaverDef.V1:1740 self.assertEqual(ops, [1741 "Add", "Assign", "Const", "Identity", "NoOp", "RestoreV2",1742 "SaveSlices", "Sub", "VariableV2"1743 ])1744 else:1745 self.assertEqual(ops, [1746 "Add", "Assign", "Const", "Identity", "NoOp", "RestoreV2", "SaveV2",1747 "Sub", "VariableV2"1748 ])1749 # Test calling stripped_op_list_for_graph directly1750 op_list = meta_graph.stripped_op_list_for_graph(meta_graph_def.graph_def)1751 self.assertEqual(ops, [o.name for o in op_list.op])1752 for o in op_list.op:1753 self.assertEqual(o.summary, "")1754 self.assertEqual(o.description, "")1755 def testImportIntoNamescope(self):1756 # Test that we can import a meta graph into a namescope.1757 test_dir = self._get_test_dir("import_into_namescope")1758 filename = os.path.join(test_dir, "ckpt")1759 image = array_ops.placeholder(dtypes.float32, [None, 784], name="image")1760 label = array_ops.placeholder(dtypes.float32, [None, 10], name="label")1761 with session.Session() as sess:1762 weights = variables.Variable(1763 random_ops.random_uniform([784, 10]), name="weights")1764 bias = variables.Variable(array_ops.zeros([10]), name="bias")1765 logit = nn_ops.relu(math_ops.matmul(image, weights) + bias, name="logits")1766 nn_ops.softmax(logit, name="prediction")1767 cost = nn_ops.softmax_cross_entropy_with_logits(labels=label,1768 logits=logit, name="cost")1769 adam.AdamOptimizer().minimize(cost, name="optimize")1770 saver = saver_module.Saver()1771 sess.run(variables.global_variables_initializer())1772 saver.save(sess, filename)1773 graph = ops_lib.Graph()1774 with session.Session(graph=graph) as sess:1775 new_saver = saver_module.import_meta_graph(1776 filename + ".meta", graph=graph, import_scope="new_model")1777 new_saver.restore(sess, filename)1778 sess.run(["new_model/​optimize"], {1779 "new_model/​image:0": np.random.random([1, 784]),1780 "new_model/​label:0": np.random.randint(1781 10, size=[1, 10])1782 })1783 def testClearDevicesOnImport(self):1784 # Test that we import a graph without its devices and run successfully.1785 with ops_lib.Graph().as_default():1786 with ops_lib.device("/​job:ps/​replica:0/​task:0/​device:GPU:0"):1787 image = array_ops.placeholder(dtypes.float32, [None, 784], name="image")1788 label = array_ops.placeholder(dtypes.float32, [None, 10], name="label")1789 weights = variables.Variable(1790 random_ops.random_uniform([784, 10]), name="weights")1791 bias = variables.Variable(array_ops.zeros([10]), name="bias")1792 logit = nn_ops.relu(math_ops.matmul(image, weights) + bias)1793 nn_ops.softmax(logit, name="prediction")1794 cost = nn_ops.softmax_cross_entropy_with_logits(labels=label,1795 logits=logit)1796 adam.AdamOptimizer().minimize(cost, name="optimize")1797 meta_graph_def = saver_module.export_meta_graph()1798 with session.Session(graph=ops_lib.Graph()) as sess:1799 saver_module.import_meta_graph(1800 meta_graph_def, clear_devices=False, import_scope="new_model")1801 # Device refers to GPU, which is not available here.1802 with self.assertRaises(errors_impl.InvalidArgumentError):1803 sess.run(variables.global_variables_initializer())1804 with session.Session(graph=ops_lib.Graph()) as sess:1805 saver_module.import_meta_graph(1806 meta_graph_def, clear_devices=True, import_scope="new_model")1807 sess.run(variables.global_variables_initializer())1808 sess.run(["new_model/​optimize"], {1809 "new_model/​image:0": np.random.random([1, 784]),1810 "new_model/​label:0": np.random.randint(1811 10, size=[1, 10])1812 })1813 def testClearDevicesOnExport(self):1814 # Test that we export a graph without its devices and run successfully.1815 with ops_lib.Graph().as_default():1816 with ops_lib.device("/​job:ps/​replica:0/​task:0/​device:GPU:0"):1817 image = array_ops.placeholder(dtypes.float32, [None, 784], name="image")1818 label = array_ops.placeholder(dtypes.float32, [None, 10], name="label")1819 weights = variables.Variable(1820 random_ops.random_uniform([784, 10]), name="weights")1821 bias = variables.Variable(array_ops.zeros([10]), name="bias")1822 logit = nn_ops.relu(math_ops.matmul(image, weights) + bias)1823 nn_ops.softmax(logit, name="prediction")1824 cost = nn_ops.softmax_cross_entropy_with_logits(labels=label,1825 logits=logit)1826 adam.AdamOptimizer().minimize(cost, name="optimize")1827 meta_graph_def = saver_module.export_meta_graph(clear_devices=True)1828 graph_io.write_graph(meta_graph_def, self.get_temp_dir(),1829 "meta_graph.pbtxt")1830 with session.Session(graph=ops_lib.Graph()) as sess:1831 saver_module.import_meta_graph(meta_graph_def, import_scope="new_model")1832 sess.run(variables.global_variables_initializer())1833 sess.run(["new_model/​optimize"], {1834 "new_model/​image:0": np.random.random([1, 784]),1835 "new_model/​label:0": np.random.randint(1836 10, size=[1, 10])1837 })1838class CheckpointReaderTest(test.TestCase):1839 _WRITE_VERSION = saver_pb2.SaverDef.V11840 def testDebugString(self):1841 # Builds a graph.1842 v0 = variables.Variable(1843 [[1, 2, 3], [4, 5, 6]], dtype=dtypes.float32, name="v0")1844 v1 = variables.Variable(1845 [[[1], [2]], [[3], [4]], [[5], [6]]], dtype=dtypes.float32, name="v1")1846 init_all_op = variables.global_variables_initializer()1847 save = saver_module.Saver(1848 {1849 "v0": v0,1850 "v1": v11851 }, write_version=self._WRITE_VERSION)1852 save_path = os.path.join(self.get_temp_dir(),1853 "ckpt_for_debug_string" + str(self._WRITE_VERSION))1854 with self.test_session() as sess:1855 sess.run(init_all_op)1856 # Saves a checkpoint.1857 save.save(sess, save_path)1858 # Creates a reader.1859 reader = pywrap_tensorflow.NewCheckpointReader(save_path)1860 # Verifies that the tensors exist.1861 self.assertTrue(reader.has_tensor("v0"))1862 self.assertTrue(reader.has_tensor("v1"))1863 debug_string = reader.debug_string()1864 # Verifies that debug string contains the right strings.1865 self.assertTrue(compat.as_bytes("v0 (DT_FLOAT) [2,3]") in debug_string)1866 self.assertTrue(compat.as_bytes("v1 (DT_FLOAT) [3,2,1]") in debug_string)1867 # Verifies get_variable_to_shape_map() returns the correct information.1868 var_map = reader.get_variable_to_shape_map()1869 self.assertEqual([2, 3], var_map["v0"])1870 self.assertEqual([3, 2, 1], var_map["v1"])1871 # Verifies get_tensor() returns the tensor value.1872 v0_tensor = reader.get_tensor("v0")1873 v1_tensor = reader.get_tensor("v1")1874 self.assertAllEqual(v0.eval(), v0_tensor)1875 self.assertAllEqual(v1.eval(), v1_tensor)1876 # Verifies get_tensor() fails for non-existent tensors.1877 with self.assertRaisesRegexp(errors.NotFoundError,1878 "v3 not found in checkpoint"):1879 reader.get_tensor("v3")1880 def testNonexistentPath(self):1881 with self.assertRaisesRegexp(errors.NotFoundError,1882 "Unsuccessful TensorSliceReader"):1883 pywrap_tensorflow.NewCheckpointReader("non-existent")1884class CheckpointReaderForV2Test(CheckpointReaderTest):1885 _WRITE_VERSION = saver_pb2.SaverDef.V21886class WriteGraphTest(test.TestCase):1887 def _get_test_dir(self, dirname):1888 test_dir = os.path.join(self.get_temp_dir(), dirname)1889 gfile.MakeDirs(test_dir)1890 return test_dir1891 def testWriteGraph(self):1892 test_dir = self._get_test_dir("write_graph_dir")1893 variables.Variable([[1, 2, 3], [4, 5, 6]], dtype=dtypes.float32, name="v0")1894 path = graph_io.write_graph(ops_lib.get_default_graph(),1895 os.path.join(test_dir, "l1"), "graph.pbtxt")1896 truth = os.path.join(test_dir, "l1", "graph.pbtxt")1897 self.assertEqual(path, truth)1898 self.assertTrue(os.path.exists(path))1899 def testRecursiveCreate(self):1900 test_dir = self._get_test_dir("deep_dir")1901 variables.Variable([[1, 2, 3], [4, 5, 6]], dtype=dtypes.float32, name="v0")1902 path = graph_io.write_graph(ops_lib.get_default_graph().as_graph_def(),1903 os.path.join(test_dir, "l1", "l2", "l3"),1904 "graph.pbtxt")1905 truth = os.path.join(test_dir, "l1", "l2", "l3", "graph.pbtxt")1906 self.assertEqual(path, truth)1907 self.assertTrue(os.path.exists(path))1908class SaverUtilsTest(test.TestCase):1909 def setUp(self):1910 self._base_dir = os.path.join(self.get_temp_dir(), "saver_utils_test")1911 gfile.MakeDirs(self._base_dir)1912 def tearDown(self):1913 gfile.DeleteRecursively(self._base_dir)1914 def testCheckpointExists(self):1915 for sharded in (False, True):1916 for version in (saver_pb2.SaverDef.V2, saver_pb2.SaverDef.V1):1917 with self.test_session(graph=ops_lib.Graph()) as sess:1918 unused_v = variables.Variable(1.0, name="v")1919 variables.global_variables_initializer().run()1920 saver = saver_module.Saver(sharded=sharded, write_version=version)1921 path = os.path.join(self._base_dir, "%s-%s" % (sharded, version))1922 self.assertFalse(1923 saver_module.checkpoint_exists(path)) # Not saved yet.1924 ckpt_prefix = saver.save(sess, path)1925 self.assertTrue(saver_module.checkpoint_exists(ckpt_prefix))1926 ckpt_prefix = saver_module.latest_checkpoint(self._base_dir)1927 self.assertTrue(saver_module.checkpoint_exists(ckpt_prefix))1928 def testGetCheckpointMtimes(self):1929 prefixes = []1930 for version in (saver_pb2.SaverDef.V2, saver_pb2.SaverDef.V1):1931 with self.test_session(graph=ops_lib.Graph()) as sess:1932 unused_v = variables.Variable(1.0, name="v")1933 variables.global_variables_initializer().run()1934 saver = saver_module.Saver(write_version=version)1935 prefixes.append(1936 saver.save(sess, os.path.join(self._base_dir, str(version))))1937 mtimes = saver_module.get_checkpoint_mtimes(prefixes)1938 self.assertEqual(2, len(mtimes))1939 self.assertTrue(mtimes[1] >= mtimes[0])1940class ScopedGraphTest(test.TestCase):1941 def _get_test_dir(self, dirname):1942 test_dir = os.path.join(self.get_temp_dir(), dirname)1943 gfile.MakeDirs(test_dir)1944 return test_dir1945 def _testScopedSave(self, test_dir, exported_filename, ckpt_filename):1946 graph = ops_lib.Graph()1947 with graph.as_default():1948 # Creates an inference graph.1949 # Hidden 11950 images = constant_op.constant(1951 1.2, dtypes.float32, shape=[100, 28], name="images")1952 with ops_lib.name_scope("hidden1"):1953 weights1 = variables.Variable(1954 random_ops.truncated_normal(1955 [28, 128], stddev=1.0 /​ math.sqrt(float(28))),1956 name="weights")1957 # The use of control_flow_ops.cond here is purely for adding test1958 # coverage the save and restore of control flow context (which doesn't1959 # make any sense here from a machine learning perspective). The typical1960 # biases is a simple Variable without the conditions.1961 biases1 = variables.Variable(1962 control_flow_ops.cond(1963 math_ops.less(random.random(), 0.5),1964 lambda: array_ops.ones([128]), lambda: array_ops.zeros([128])),1965 name="biases")1966 hidden1 = nn_ops.relu(math_ops.matmul(images, weights1) + biases1)1967 # Hidden 21968 with ops_lib.name_scope("hidden2"):1969 weights2 = variables.Variable(1970 random_ops.truncated_normal(1971 [128, 32], stddev=1.0 /​ math.sqrt(float(128))),1972 name="weights")1973 # The use of control_flow_ops.while_loop here is purely for adding test1974 # coverage the save and restore of control flow context (which doesn't1975 # make any sense here from a machine learning perspective). The typical1976 # biases is a simple Variable without the conditions.1977 def loop_cond(it, _):1978 return it < 21979 def loop_body(it, biases2):1980 biases2 += constant_op.constant(0.1, shape=[32])1981 return it + 1, biases21982 _, biases2 = control_flow_ops.while_loop(loop_cond, loop_body, [1983 constant_op.constant(0), variables.Variable(array_ops.zeros([32]))1984 ])1985 hidden2 = nn_ops.relu(math_ops.matmul(hidden1, weights2) + biases2)1986 # Linear1987 with ops_lib.name_scope("softmax_linear"):1988 weights3 = variables.Variable(1989 random_ops.truncated_normal(1990 [32, 10], stddev=1.0 /​ math.sqrt(float(32))),1991 name="weights")1992 biases3 = variables.Variable(array_ops.zeros([10]), name="biases")1993 logits = math_ops.matmul(hidden2, weights3) + biases31994 ops_lib.add_to_collection("logits", logits)1995 # Adds user_defined proto in three formats: string, bytes and Any.1996 # Any proto should just pass through.1997 queue_runner = queue_runner_pb2.QueueRunnerDef(queue_name="test_queue")1998 ops_lib.add_to_collection("user_defined_string_collection",1999 str(queue_runner))2000 ops_lib.add_to_collection("user_defined_bytes_collection",2001 queue_runner.SerializeToString())2002 any_buf = Any()2003 any_buf.Pack(queue_runner)2004 ops_lib.add_to_collection("user_defined_any_collection", any_buf)2005 _, var_list = meta_graph.export_scoped_meta_graph(2006 filename=os.path.join(test_dir, exported_filename),2007 graph=ops_lib.get_default_graph(),2008 export_scope="hidden1")2009 self.assertEqual(["biases:0", "weights:0"], sorted(var_list.keys()))2010 with self.test_session(graph=graph) as sess:2011 sess.run(variables.global_variables_initializer())2012 saver = saver_module.Saver(var_list=var_list, max_to_keep=1)2013 saver.save(sess, os.path.join(test_dir, ckpt_filename), write_state=False)2014 def _testScopedRestore(self, test_dir, exported_filename,2015 new_exported_filename, ckpt_filename):2016 graph = ops_lib.Graph()2017 # Create all the missing inputs.2018 with graph.as_default():2019 new_image = constant_op.constant(2020 1.2, dtypes.float32, shape=[100, 28], name="images")2021 var_list = meta_graph.import_scoped_meta_graph(2022 os.path.join(test_dir, exported_filename),2023 graph=graph,2024 input_map={"$unbound_inputs_images": new_image},2025 import_scope="new_hidden1")2026 self.assertEqual(["biases:0", "weights:0"], sorted(var_list.keys()))2027 hidden1 = graph.as_graph_element("new_hidden1/​Relu:0")2028 weights1 = graph.as_graph_element("new_hidden1/​weights:0")2029 biases1 = graph.as_graph_element("new_hidden1/​biases:0")2030 with graph.as_default():2031 # Hidden 22032 with ops_lib.name_scope("hidden2"):2033 weights = variables.Variable(2034 random_ops.truncated_normal(2035 [128, 32], stddev=1.0 /​ math.sqrt(float(128))),2036 name="weights")2037 # The use of control_flow_ops.while_loop here is purely for adding test2038 # coverage the save and restore of control flow context (which doesn't2039 # make any sense here from a machine learning perspective). The typical2040 # biases is a simple Variable without the conditions.2041 def loop_cond(it, _):2042 return it < 22043 def loop_body(it, biases):2044 biases += constant_op.constant(0.1, shape=[32])2045 return it + 1, biases2046 _, biases = control_flow_ops.while_loop(loop_cond, loop_body, [2047 constant_op.constant(0), variables.Variable(array_ops.zeros([32]))2048 ])2049 hidden2 = nn_ops.relu(math_ops.matmul(hidden1, weights) + biases)2050 # Linear2051 with ops_lib.name_scope("softmax_linear"):2052 weights = variables.Variable(2053 random_ops.truncated_normal(2054 [32, 10], stddev=1.0 /​ math.sqrt(float(32))),2055 name="weights")2056 biases = variables.Variable(array_ops.zeros([10]), name="biases")2057 logits = math_ops.matmul(hidden2, weights) + biases2058 ops_lib.add_to_collection("logits", logits)2059 # The rest of the variables.2060 rest_variables = list(2061 set(variables.global_variables()) - set(var_list.keys()))2062 init_rest_op = variables.initialize_variables(rest_variables)2063 with self.test_session(graph=graph) as sess:2064 saver = saver_module.Saver(var_list=var_list, max_to_keep=1)2065 saver.restore(sess, os.path.join(test_dir, ckpt_filename))2066 # Verify that we have restored weights1 and biases1.2067 sess.run([weights1, biases1])2068 # Initialize the rest of the variables and run logits.2069 sess.run(init_rest_op)2070 sess.run(logits)2071 # Verifies that we can save the subgraph under "hidden1" and restore it2072 # into "new_hidden1" in the new graph.2073 def testScopedSaveAndRestore(self):2074 test_dir = self._get_test_dir("scoped_export_import")2075 ckpt_filename = "ckpt"2076 self._testScopedSave(test_dir, "exported_hidden1.pbtxt", ckpt_filename)2077 self._testScopedRestore(test_dir, "exported_hidden1.pbtxt",2078 "exported_new_hidden1.pbtxt", ckpt_filename)2079 # Verifies that we can copy the subgraph under "hidden1" and copy it2080 # to different name scope in the same graph or different graph.2081 def testCopyScopedGraph(self):2082 test_dir = self._get_test_dir("scoped_copy")2083 saver0_ckpt = os.path.join(test_dir, "saver0.ckpt")2084 graph1 = ops_lib.Graph()2085 with graph1.as_default():2086 with ops_lib.name_scope("hidden1"):2087 images = constant_op.constant(2088 1.0, dtypes.float32, shape=[3, 2], name="images")2089 weights1 = variables.Variable(2090 [[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]], name="weights")2091 biases1 = variables.Variable([0.1] * 3, name="biases")2092 nn_ops.relu(math_ops.matmul(images, weights1) + biases1, name="relu")2093 # Run the graph and save scoped checkpoint.2094 with self.test_session(graph=graph1) as sess:2095 sess.run(variables.global_variables_initializer())2096 _, var_list_1 = meta_graph.export_scoped_meta_graph(2097 export_scope="hidden1")2098 saver = saver_module.Saver(var_list=var_list_1, max_to_keep=1)2099 saver.save(sess, saver0_ckpt, write_state=False)2100 expected = np.reshape([[5.0999999, 7.0999999, 9.10000038] * 3], (3, 3))2101 # Verifies copy to the same graph with the same name fails.2102 with graph1.as_default():2103 with self.assertRaisesWithPredicateMatch(2104 ValueError, lambda e: "need to be different" in str(e)):2105 meta_graph.copy_scoped_meta_graph(2106 from_scope="hidden1", to_scope="hidden1")2107 # Verifies copy to the same graph.2108 with graph1.as_default():2109 var_list_2 = meta_graph.copy_scoped_meta_graph(2110 from_scope="hidden1", to_scope="hidden2")2111 with self.test_session(graph=graph1) as sess:2112 saver1 = saver_module.Saver(var_list=var_list_1, max_to_keep=1)2113 saver1.restore(sess, saver0_ckpt)2114 saver2 = saver_module.Saver(var_list=var_list_2, max_to_keep=1)2115 saver2.restore(sess, saver0_ckpt)2116 self.assertAllClose(expected, sess.run("hidden1/​relu:0"))2117 self.assertAllClose(expected, sess.run("hidden2/​relu:0"))2118 # Verifies copy to differen graph.2119 graph2 = ops_lib.Graph()2120 new_var_list_1 = meta_graph.copy_scoped_meta_graph(2121 from_scope="hidden1",2122 to_scope="new_hidden1",2123 from_graph=graph1,2124 to_graph=graph2)2125 with self.test_session(graph=graph2) as sess:2126 saver3 = saver_module.Saver(var_list=new_var_list_1, max_to_keep=1)2127 saver3.restore(sess, saver0_ckpt)2128 self.assertAllClose(expected, sess.run("new_hidden1/​relu:0"))2129 def testExportGraphDefWithScope(self):2130 test_dir = self._get_test_dir("export_graph_def")2131 saver0_ckpt = os.path.join(test_dir, "saver0.ckpt")2132 graph1 = ops_lib.Graph()2133 with graph1.as_default():2134 with ops_lib.name_scope("hidden1"):2135 images = constant_op.constant(2136 1.0, dtypes.float32, shape=[3, 2], name="images")2137 weights1 = variables.Variable(2138 [[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]], name="weights")2139 biases1 = variables.Variable([0.1] * 3, name="biases")2140 nn_ops.relu(math_ops.matmul(images, weights1) + biases1, name="relu")2141 # Run the graph and save scoped checkpoint.2142 with self.test_session(graph=graph1) as sess:2143 sess.run(variables.global_variables_initializer())2144 _, var_list_1 = meta_graph.export_scoped_meta_graph(2145 graph_def=graph1.as_graph_def(), export_scope="hidden1")2146 saver = saver_module.Saver(var_list=var_list_1, max_to_keep=1)2147 saver.save(sess, saver0_ckpt, write_state=False)2148 expected = np.reshape([[5.0999999, 7.0999999, 9.10000038] * 3], (3, 3))2149 # Verifies that we can run successfully after restoring.2150 graph2 = ops_lib.Graph()2151 new_var_list_1 = meta_graph.copy_scoped_meta_graph(2152 from_scope="hidden1",2153 to_scope="new_hidden1",2154 from_graph=graph1,2155 to_graph=graph2)2156 with self.test_session(graph=graph2) as sess:2157 saver3 = saver_module.Saver(var_list=new_var_list_1, max_to_keep=1)2158 saver3.restore(sess, saver0_ckpt)2159 self.assertAllClose(expected, sess.run("new_hidden1/​relu:0"))2160 def testSerializeSaverWithScope(self):2161 test_dir = self._get_test_dir("export_graph_def")2162 saver1_ckpt = os.path.join(test_dir, "saver1.ckpt")2163 saver2_ckpt = os.path.join(test_dir, "saver2.ckpt")2164 graph = ops_lib.Graph()2165 with graph.as_default():2166 with ops_lib.name_scope("hidden1"):2167 variable1 = variables.Variable([1.0], name="variable1")2168 saver1 = saver_module.Saver(var_list=[variable1])2169 graph.add_to_collection(ops_lib.GraphKeys.SAVERS, saver1)2170 with ops_lib.name_scope("hidden2"):2171 variable2 = variables.Variable([2.0], name="variable2")2172 saver2 = saver_module.Saver(var_list=[variable2], name="hidden2/​")2173 graph.add_to_collection(ops_lib.GraphKeys.SAVERS, saver2)2174 with self.test_session(graph=graph) as sess:2175 variables.global_variables_initializer().run()2176 saver1.save(sess, saver1_ckpt, write_state=False)2177 saver2.save(sess, saver2_ckpt, write_state=False)2178 graph1 = ops_lib.Graph()2179 var_dict1 = meta_graph.copy_scoped_meta_graph(2180 from_scope="hidden1",2181 to_scope="new_hidden1",2182 from_graph=graph,2183 to_graph=graph1)2184 self.assertEqual(1, len(var_dict1))2185 saver_list1 = graph1.get_collection(ops_lib.GraphKeys.SAVERS)2186 self.assertEqual(1, len(saver_list1))2187 with self.test_session(graph=graph1) as sess:2188 saver_list1[0].restore(sess, saver1_ckpt)2189 self.assertEqual(1.0, var_dict1["variable1:0"].eval())2190 graph2 = ops_lib.Graph()2191 var_dict2 = meta_graph.copy_scoped_meta_graph(2192 from_scope="hidden2",2193 to_scope="new_hidden2",2194 from_graph=graph,2195 to_graph=graph2)2196 self.assertEqual(1, len(var_dict2))2197 saver_list2 = graph2.get_collection(ops_lib.GraphKeys.SAVERS)2198 self.assertEqual(1, len(saver_list2))2199 with self.test_session(graph=graph2) as sess:2200 saver_list2[0].restore(sess, saver2_ckpt)2201 self.assertEqual(2.0, var_dict2["variable2:0"].eval())2202# TODO(b/​64763924): Remove after Jan 1st 2018.2203class LenientNamesTest(test.TestCase):2204 def setUp(self):2205 super(LenientNamesTest, self).setUp()2206 os.putenv("TF_SAVER_LENIENT_NAMES", "True")2207 def tearDown(self):2208 os.putenv("TF_SAVER_LENIENT_NAMES", "")2209 super(LenientNamesTest, self).tearDown()2210 def testSaveRestore(self):2211 save_path = os.path.join(self.get_temp_dir(), "basic_save_restore")2212 # Build a graph with 2 parameter nodes, and Save and2213 # Restore nodes for them.2214 v0 = variables.Variable(10.0, name="v0")2215 v1 = variables.Variable(20.0, name="v1")2216 v2 = saver_test_utils.CheckpointedOp(name="v2")2217 v2_init = v2.insert("k1", 30.0)2218 save = saver_module.Saver(2219 {2220 "v0:0": v0,2221 "v1": v1,2222 "v2": v2.saveable2223 }, restore_sequentially=True)2224 init_all_op = [variables.global_variables_initializer(), v2_init]2225 with self.test_session() as sess:2226 sess.run(init_all_op)2227 save.save(sess, save_path)2228 with self.test_session() as sess:2229 v0 = variables.Variable(-1.0, name="v0")2230 v1 = variables.Variable(-1.0, name="v1")2231 v2 = saver_test_utils.CheckpointedOp(name="v2")2232 save = saver_module.Saver({"v0": v0, "v1": v1, "v2": v2.saveable})2233 save.restore(sess, save_path)2234 # Check that the parameter nodes have been restored.2235 self.assertEqual(10.0, v0.eval())2236 self.assertEqual(20.0, v1.eval())2237 self.assertEqual(b"k1", v2.keys().eval())2238 self.assertEqual(30.0, v2.values().eval())2239if __name__ == "__main__":...

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whole_game_work_in_progress.py

Source:whole_game_work_in_progress.py Github

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1import pygame2from buildings import Factory3from buildings import Windturbine4from buildings import Cleaning_station56pygame.init()78screen = pygame.display.set_mode((800, 600))9background_color = (101, 56, 24)10screen.fill(background_color)11clock = pygame.time.Clock()12counter = 013income = 0141516def button(screen, position, text):17 font = pygame.font.SysFont("Arial", 50)18 text_render = font.render(text, 1, (0, 0, 0))19 x, y, w, h = text_render.get_rect()20 x, y = position21 pygame.draw.line(screen, (50, 50, 50), (x, y + h), (x + w, y + h), 5)22 pygame.draw.line(screen, (50, 50, 50), (x + w, y + h), [x + w, y], 5)23 pygame.draw.rect(screen, (128, 128, 128), (x, y, w, h))24 return screen.blit(text_render, (x, y))252627def button2(screen, position, text, color):28 global text_render, Button_Img29 font = pygame.font.SysFont("Arial", 24)30 if color == "blue":31 text_render = font.render(text, 1, (0, 0, 255))32 elif color == "green":33 text_render = font.render(text, 1, (0, 255, 0))34 elif color == "red":35 text_render = font.render(text, 1, (255, 0, 0))36 elif color == "pink":37 text_render = font.render(text, 1, (255, 182, 193))38 x, y, w, h = text_render.get_rect()39 x, y = position40 pygame.draw.line(screen, (50, 50, 50), (x, y + h), (x + w, y + h), 5)41 pygame.draw.line(screen, (50, 50, 50), (x + w, y + h), [x + w, y], 5)42 pygame.draw.rect(screen, (100, 100, 100), (x, y, w, h))43 return screen.blit(text_render, (x, y))444546def buildings_menu():47 global buy_factory, buy_cleaning, buy_windturbine, upgrade48 buy_factory = button2(screen, (500, 100), " BUY FACTORY: 1000 ", "red")49 buy_cleaning = button2(screen, (500, 150), " BUY CL. STATION: 3500 ", "blue")50 buy_windturbine = button2(screen, (500, 200), " BUY WINDMILL: 2000 ", "green")51 upgrade = button2(screen, (500, 300), " UPGRADE: 10000 ", "red")525354def buy_menu():55 global buy_land56 buy_land = button2(screen, (500, 250), " BUY: 1500 ", "pink")575859def menu():60 global buy_factory, buy_cleaning, buy_windturbine, buy_land, counter, upgrade, clock, income, save_i, save_j, Button_Img61 factory = Factory(1000, 0.03, 0, 1.5)62 windturbine = Windturbine(2000, 0, 0, 0.5)63 cleaning_station = Cleaning_station(3500, 0.055, 0, 0)64 color = (101, 56, 24)65 money = 7000066 counter_factory = 067 counter_windturbine = 068 counter_cleaning_station = 069 counter_factory_upgrade = 070 counter_cleaning_station_upgrade = 071 counter_windturbine_upgrade = 072 polution = 073 b = [[11, 12, 5, 2], [15, 6, 10, 3], [10, 8, 12, 6], [12, 15, 8, 69], [12, 15, 8, 69]]74 bought = [[0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0]]7576 def display_text():77 font = pygame.font.SysFont("Stencil", 40)7879 bar_color = (119, 136, 153)80 pygame.draw.rect(screen, color, pygame.Rect(610, 35, 170, 45))81 pygame.display.flip()82 score_display = font.render(f"MONEY : {money}", 1, (8, 255, 8))83 screen.blit(score_display, (450, 35))84 pygame.draw.rect(screen, bar_color, [80, 30, polution * 3, 30])8586 pygame.display.update()8788 for i in range(4): # i e redove89 for j in range(4): # j e koloni90 if i == 1:91 b[i][j] = button(screen, ((90 * (j + 1)), 100), " ") # first one x,second one y92 elif i == 2:93 b[i][j] = button(screen, ((90 * (j + 1)), 200), " ")94 elif i == 3:95 b[i][j] = button(screen, ((90 * (j + 1)), 300), " ")96 else:97 b[i][j] = button(screen, ((90 * (j + 1)), 400), " ")98 running = 099 while running == 0:100 mx, my = pygame.mouse.get_pos()101 money += income102 if counter_cleaning_station > 0 or counter_cleaning_station_upgrade > 0 and polution > 0:103 polution = polution + factory.polution * (counter_factory + counter_factory_upgrade) - (cleaning_station.polution * counter_cleaning_station + 3 * cleaning_station.polution * counter_cleaning_station_upgrade)104 polution = round(polution, 2)105 elif counter_cleaning_station == 0 and counter_cleaning_station_upgrade == 0:106 polution = polution + factory.polution * (counter_factory + counter_factory_upgrade)107 elif polution <= 0:108 polution = polution + 0109110 display_text()111112 if polution > 100000000:113 income = 0114 money = 0115 running = 1116117 for event in pygame.event.get():118 if event.type == pygame.QUIT:119 pygame.quit()120 if event.type == pygame.MOUSEBUTTONDOWN:121 for i in range(4):122 for j in range(4):123 if b[i][j].collidepoint(mx, my):124 buy_menu()125 buildings_menu()126 save_i = i127 save_j = j128 pass129130 if buy_land.collidepoint(mx, my) and money >= 1500 and bought[save_i][save_j] == 0:131 pygame.draw.rect(screen, (255, 182, 193), b[save_i][save_j])132 money = money - 1500133 bought[save_i][save_j] = 10134 if buy_factory.collidepoint(mx, my) and money >= factory.cost and bought[save_i][save_j] == 10 and bought[save_i][save_j] != 11 and bought[save_i][save_j] != 12 and bought[save_i][save_j] != 13 and bought[save_i][save_j] != 21 and bought[save_i][save_j] != 22 and bought[save_i][save_j] != 23:135 pygame.draw.rect(screen, (255, 0, 0), b[save_i][save_j])136 money = money - factory.cost137 counter_factory = counter_factory + 1138 bought[save_i][save_j] = 11139 Button_Img = pygame.image.load("buildings/​factory.png")140 if save_j <= 3:141 screen.blit(Button_Img, (90 * (save_j + 1), 100 * save_i))142 elif save_i == 3:143 screen.blit(Button_Img, (90 * (save_j + 1), 100 * save_i))144 if buy_cleaning.collidepoint(mx, my) and money >= cleaning_station.cost and bought[save_i][save_j] == 10 and bought[save_i][save_j] != 11 and bought[save_i][save_j] != 12 and bought[save_i][save_j] != 13 and bought[save_i][save_j] != 21 and bought[save_i][save_j] != 22 and bought[save_i][save_j] != 23:145 pygame.draw.rect(screen, (173, 216, 230), b[save_i][save_j])146 money = money - cleaning_station.cost147 counter_cleaning_station = counter_cleaning_station + 1148 bought[save_i][save_j] = 12149 Button_Img = pygame.image.load("buildings/​cleaning.png")150 if save_j <= 2:151 screen.blit(Button_Img, (90 * (save_j + 1), 100 * save_i))152 elif save_i == 3:153 screen.blit(Button_Img, (90 * (save_j + 1), 400))154 if buy_windturbine.collidepoint(mx, my) and money >= windturbine.cost and bought[save_i][save_j] == 10 and bought[save_i][save_j] != 11 and bought[save_i][save_j] != 12 and bought[save_i][save_j] != 13 and bought[save_i][save_j] != 21 and bought[save_i][save_j] != 22 and bought[save_i][save_j] != 23:155 pygame.draw.rect(screen, (0, 255, 0), b[save_i][save_j])156 money = money - windturbine.cost157 counter_windturbine = counter_windturbine + 1158 bought[save_i][save_j] = 13159 Button_Img = pygame.image.load("buildings/​windturbine.jpeg")160 if save_j <= 2:161 screen.blit(Button_Img, (90 * (save_j + 1), 100 * save_i))162 elif save_j == 3:163 screen.blit(Button_Img, (90 * (save_j + 1), 400))164 if upgrade.collidepoint(mx, my) and money >= 10000 and bought[save_i][save_j] == 11:165 pygame.draw.rect(screen, (139, 0, 0), b[save_i][save_j])166 money = money - 10000167 counter_factory_upgrade = counter_factory_upgrade + 1168 counter_factory = counter_factory - 1169 bought[save_i][save_j] = 21170 Button_Img = pygame.image.load("buildings/​factory_upgrade.png")171 if save_j <= 2:172 screen.blit(Button_Img, (90 * (save_j + 1), 100 * save_i))173 elif save_j == 3:174 screen.blit(Button_Img, (90 * (save_j + 1), 400))175 if upgrade.collidepoint(mx, my) and money >= 10000 and bought[save_i][save_j] == 12:176 pygame.draw.rect(screen, (0, 0, 255), b[save_i][save_j])177 money = money - 10000178 counter_cleaning_station_upgrade = counter_cleaning_station_upgrade + 1179 counter_cleaning_station = counter_cleaning_station - 1180 bought[save_i][save_j] = 22181 if upgrade.collidepoint(mx, my) and money >= 10000 and bought[save_i][save_j] == 13:182 pygame.draw.rect(screen, (149, 255, 128), b[save_i][save_j])183 money = money - 10000184 counter_windturbine_upgrade = counter_windturbine_upgrade + 1185 counter_windturbine = counter_windturbine - 1186 bought[save_i][save_j] = 23187 Button_Img = pygame.image.load("buildings/​windturbine_upgrade.jpg")188 if save_j <= 2:189 screen.blit(Button_Img, (90 * (save_j + 1), 100 * save_i))190 elif save_i == 3:191 screen.blit(Button_Img, (90 * (save_j + 1), 400))192 else:193 pass194195 income = factory.income * counter_factory + windturbine.income * counter_windturbine + 1.5 * counter_factory_upgrade * factory.income + 1.5 * counter_windturbine_upgrade * windturbine.income196 money = round(money, 0)197 clock.tick(60)198199 ...

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populate_database.py

Source:populate_database.py Github

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...33 python_module='tools.Setup_workdir.setupWorkDir',34 hidden=True,35 tool_folder_name="Setup_workdir"36 )37module1.save()38module2 = Module(name="Untar",39 type='0',40 filter='.*(\.tar)',41 form=[{"type":"checkbox", "label":"Verbose", "identifier":"verbose", "value": "-v"}],42 description="Untar all .tar fieles into the current folder",43 tool_folder_name="Untar_archive",44 command="tar xf #file -C #workdir #verbose ",45 hidden=True46 )47module2.save()48module3 = Module(name="ClamAV",49 type='0',50 form=[{"type":"checkbox", "label":"Only show infected files", "identifier":"only_found", "value":"-i"},{"type":"checkbox", "label":"Remove infected files", "identifier":"remove", "value":"--remove"}],51 # command='[{"value":"clamscan","type":"text"},{"type":"text","value":"-r"},{"value":"-i","type":"var","name":"only_found"},{"value":"--remove","type":"var","name":"remove"},{"type":"var","name":"workdir"}]',52 command="clamscan -r #only_found #remove #workdir",53 tool_folder_name="ClamAV"54 )55module3.save()56module8 = Module(name="DROID",57 type='3',58 form=[],59 command="/​run.sh \"#file\"",60 filter='.*',61 tool_folder_name="SMART_DROID",62 docker_mount_point="/​workdir",63 resultFilter=[{"type": "Containing","value": "[\\w\\W]*Missmatch: \"false\"[\\w\\W]*"},{"type": "Not containing","value": "[\\w\\W]*Missmatch: \"true\"[\\w\\W]*"}]64 )65module8.save()66module11 = Module(name="Unoconv",67 type='3',68 form=[],69 command="UNOPATH=/​usr/​lib/​Libreoffice /​usr/​bin/​python3 /​usr/​bin/​unoconv -f pdf -e SelectPdfVersion=1 \"#file\"",70 # command="seq -s= 100000|tr -d '[:digit:]'",71 filter='.*(\\.(doc|docx))$',72 tool_folder_name="SMART_UNOCONV",73 docker_mount_point="/​workdir",74 parallell_jobs=675 )76module11.save()77module12 = Module(name="Verapdf",78 type='3',79 form=[],80 command="verapdf -f 1a \"#file\"",81 filter='.*(\\.pdf)',82 tool_folder_name="SMART_VERAPDF",83 docker_mount_point="/​workdir",84 resultFilter=[{"type":"Containing", "value": "[\\w\\W]*compliant=\"1\"[\\w\\W]*"}],85 parallell_jobs=686 )87module12.save()88# setup default templates89template1 = Template(name="Default Start", hidden=True)90template1.save()91process2 = Process(order=1,92 template=template1,93 module=module2,94 value={"verbose": True}95 )96process2.save()97template2 = Template(name="Default Done", hidden=True)98template2.save()99template3 = Template(name="Empty template")100template3.save()101template4 = Template(name="Convert pdf")102template4.save()103process = Process(order=0,104 template=template4,105 module=module11) # unoconv106process.save()107process = Process(order=1,108 template=template4,109 module=module12) # verapdf110process.save()111# create default variables112var = Variable(name="total_number_of_files", data="0")113var.save()114var = Variable(name="total_size", data="0")115var.save()116var = Variable(name="total_number_of_packages", data="0")117var.save()118var = Variable(name="total_number_of_errors", data="0")119var.save()120# system variables121var = Variable(name="work_dir_path", data="/​code/​workdir")122var.save()123var = Variable(name="packages_path", data="/​code/​packages")124var.save()125var = Variable(name="tools_path", data="/​code/​tools")126var.save()127var = Variable(name="premis_file_name", data="log/​app_log.xml")128var.save()129var = Variable(name="work_dir_path_host", data="/​Users/​axenu/​Projects/​Sydarkivera/​APP/​workdir")130var.save()131var = Variable(name="premis_template_path", data="/​code/​templates/​premis.json")132var.save()133var = Variable(name="premis_event_template_path", data="/​code/​templates/​premisEvent.json")134var.save()135# default test data, TODO remove in production136# ftype = FileType(name="PDF", errors=3, total=100, size=1203000)137# ftype.save()138# ftype = FileType(name="JPG", errors=33, total=10, size=12033400)139# ftype.save()140# ftype = FileType(name="XML", errors=0, total=43, size=120340)141# ftype.save()142# ftype = FileType(name="XSD", errors=0, total=12, size=120300123)143# ftype.save()144# ftype = FileType(name="sdf", errors=0, total=12, size=120300123)145# ftype.save()146# ftype = FileType(name="Xdh4eSD", errors=0, total=12, size=120300123)147# ftype.save()148# ftype = FileType(name="fgdh", errors=0, total=12, size=120300123)149# ftype.save()150# ftype = FileType(name="wert", errors=0, total=12, size=120300123)151# ftype.save()152# graph = GraphData(date=(datetime.date.today() - datetime.timedelta(days=21)), size=1110000000, count=37954)153# graph.save()154# graph = GraphData(date=(datetime.date.today() - datetime.timedelta(days=14)), size=5834400000, count=9754)155# graph.save()156# graph = GraphData(date=(datetime.date.today() - datetime.timedelta(days=7)), size=2340000000, count=751)157# graph.save()158# graph = GraphData(date=datetime.date.today(), size=300000000, count=3452)159# graph.save()160#create default docker images161# image = DockerImage(name="vera_pdf", mountpoint="/​workdir", label="verapdf")162# image.save()163# module12.dockerImage = image164# module12.save()165image = DockerImage(name="axenu/​app-worker-droid", mountpoint="/​workdir", label="Droid")166image.save()167module8.dockerImage = image168module8.save()169image = DockerImage(name="axenu/​app-worker-unoconv", mountpoint="/​workdir", label="Unoconv")170image.save()171module11.dockerImage = image172module11.save()173image = DockerImage(name="axenu/​app-worker-verapdf", mountpoint="/​workdir", label="VeraPDF")174image.save()175module12.dockerImage = image176module12.save()177# create default admin users178User.objects.all().delete()179user = User.objects.create_user('admin', 'simon@axenu.com', 'admin')180user.is_superuser = True181user.is_staff = True182# user.role = 2183user.save()184print('populate_databse finished')185#create new package.186# package1 = Package(name="demo paket 1", path="/​Users/​axenu/​Sydarkivera/​toolbox/​paket/​af268c33-5ba8-4af5-9a44-039b10126835.tar", file_name="af268c33-5ba8-4af5-9a44-039b10126835.tar", status=0)187# package1.save()188# create some processes189# process1 = Process(order=1, package=package1, module=module1, value='{}')190# process1.save()191# process2 = Process(order=2, package=package1, module=module2, value='{}')...

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urls.py

Source:urls.py Github

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1from django.urls import path, include2from . import views3from .import HodViews, StaffViews, StudentViews4urlpatterns = [5 path('', views.loginPage, name="login"),6 # path('accounts/​', include('django.contrib.auth.urls')),7 path('doLogin/​', views.doLogin, name="doLogin"),8 path('get_user_details/​', views.get_user_details, name="get_user_details"),9 path('logout_user/​', views.logout_user, name="logout_user"),10 path('admin_home/​', HodViews.admin_home, name="admin_home"),11 path('add_staff/​', HodViews.add_staff, name="add_staff"),12 path('add_staff_save/​', HodViews.add_staff_save, name="add_staff_save"),13 path('manage_staff/​', HodViews.manage_staff, name="manage_staff"),14 path('edit_staff/​<staff_id>/​', HodViews.edit_staff, name="edit_staff"),15 path('edit_staff_save/​', HodViews.edit_staff_save, name="edit_staff_save"),16 path('delete_staff/​<staff_id>/​', HodViews.delete_staff, name="delete_staff"),17 path('add_course/​', HodViews.add_course, name="add_course"),18 path('add_course_save/​', HodViews.add_course_save, name="add_course_save"),19 path('manage_course/​', HodViews.manage_course, name="manage_course"),20 path('edit_course/​<course_id>/​', HodViews.edit_course, name="edit_course"),21 path('edit_course_save/​', HodViews.edit_course_save, name="edit_course_save"),22 path('delete_course/​<course_id>/​', HodViews.delete_course, name="delete_course"),23 path('manage_session/​', HodViews.manage_session, name="manage_session"),24 path('add_session/​', HodViews.add_session, name="add_session"),25 path('add_session_save/​', HodViews.add_session_save, name="add_session_save"),26 path('edit_session/​<session_id>', HodViews.edit_session, name="edit_session"),27 path('edit_session_save/​', HodViews.edit_session_save, name="edit_session_save"),28 path('delete_session/​<session_id>/​', HodViews.delete_session, name="delete_session"),29 path('add_student/​', HodViews.add_student, name="add_student"),30 path('add_student_save/​', HodViews.add_student_save, name="add_student_save"),31 path('edit_student/​<student_id>', HodViews.edit_student, name="edit_student"),32 path('edit_student_save/​', HodViews.edit_student_save, name="edit_student_save"),33 path('manage_student/​', HodViews.manage_student, name="manage_student"),34 path('delete_student/​<student_id>/​', HodViews.delete_student, name="delete_student"),35 path('add_subject/​', HodViews.add_subject, name="add_subject"),36 path('add_subject_save/​', HodViews.add_subject_save, name="add_subject_save"),37 path('manage_subject/​', HodViews.manage_subject, name="manage_subject"),38 path('edit_subject/​<subject_id>/​', HodViews.edit_subject, name="edit_subject"),39 path('edit_subject_save/​', HodViews.edit_subject_save, name="edit_subject_save"),40 path('delete_subject/​<subject_id>/​', HodViews.delete_subject, name="delete_subject"),41 path('check_email_exist/​', HodViews.check_email_exist, name="check_email_exist"),42 path('check_username_exist/​', HodViews.check_username_exist, name="check_username_exist"),43 path('student_feedback_message/​', HodViews.student_feedback_message, name="student_feedback_message"),44 path('student_feedback_message_reply/​', HodViews.student_feedback_message_reply, name="student_feedback_message_reply"),45 path('staff_feedback_message/​', HodViews.staff_feedback_message, name="staff_feedback_message"),46 path('staff_feedback_message_reply/​', HodViews.staff_feedback_message_reply, name="staff_feedback_message_reply"),47 path('student_leave_view/​', HodViews.student_leave_view, name="student_leave_view"),48 path('student_leave_approve/​<leave_id>/​', HodViews.student_leave_approve, name="student_leave_approve"),49 path('student_leave_reject/​<leave_id>/​', HodViews.student_leave_reject, name="student_leave_reject"),50 path('staff_leave_view/​', HodViews.staff_leave_view, name="staff_leave_view"),51 path('staff_leave_approve/​<leave_id>/​', HodViews.staff_leave_approve, name="staff_leave_approve"),52 path('staff_leave_reject/​<leave_id>/​', HodViews.staff_leave_reject, name="staff_leave_reject"),53 path('admin_view_attendance/​', HodViews.admin_view_attendance, name="admin_view_attendance"),54 path('admin_get_attendance_dates/​', HodViews.admin_get_attendance_dates, name="admin_get_attendance_dates"),55 path('admin_get_attendance_student/​', HodViews.admin_get_attendance_student, name="admin_get_attendance_student"),56 path('admin_profile/​', HodViews.admin_profile, name="admin_profile"),57 path('admin_profile_update/​', HodViews.admin_profile_update, name="admin_profile_update"),58 path('add_project/​', HodViews.add_project, name="add_project"),59 path('add_project_save/​', HodViews.add_project_save, name="add_project_save"),60 path('manage_project/​', HodViews.manage_project, name="manage_project"),61 path('edit_project/​<project_id>/​', HodViews.edit_project, name="edit_project"),62 path('edit_project_save/​', HodViews.edit_project_save, name="edit_project_save"),63 path('delete_project/​<project_id>/​', HodViews.delete_project, name="delete_project"),64 65 # URLS for Staff66 path('staff_home/​', StaffViews.staff_home, name="staff_home"),67 path('staff_take_attendance/​', StaffViews.staff_take_attendance, name="staff_take_attendance"),68 path('get_students/​', StaffViews.get_students, name="get_students"),69 path('save_attendance_data/​', StaffViews.save_attendance_data, name="save_attendance_data"),70 path('staff_update_attendance/​', StaffViews.staff_update_attendance, name="staff_update_attendance"),71 path('get_attendance_dates/​', StaffViews.get_attendance_dates, name="get_attendance_dates"),72 path('get_attendance_student/​', StaffViews.get_attendance_student, name="get_attendance_student"),73 path('update_attendance_data/​', StaffViews.update_attendance_data, name="update_attendance_data"),74 path('staff_apply_leave/​', StaffViews.staff_apply_leave, name="staff_apply_leave"),75 path('staff_apply_leave_save/​', StaffViews.staff_apply_leave_save, name="staff_apply_leave_save"),76 path('staff_feedback/​', StaffViews.staff_feedback, name="staff_feedback"),77 path('staff_feedback_save/​', StaffViews.staff_feedback_save, name="staff_feedback_save"),78 path('staff_profile/​', StaffViews.staff_profile, name="staff_profile"),79 path('staff_profile_update/​', StaffViews.staff_profile_update, name="staff_profile_update"),80 path('staff_add_result/​', StaffViews.staff_add_result, name="staff_add_result"),81 path('staff_add_result_save/​', StaffViews.staff_add_result_save, name="staff_add_result_save"),82 path('staff_project_view/​', StaffViews.project_view, name="project_view"),83 path('staff_eachproject_view/​<subject_id>/​', StaffViews.eachproject_view, name="eachproject_view"),84 # URSL for Student85 path('student_home/​', StudentViews.student_home, name="student_home"),86 path('student_view_attendance/​', StudentViews.student_view_attendance, name="student_view_attendance"),87 path('student_view_attendance_post/​', StudentViews.student_view_attendance_post, name="student_view_attendance_post"),88 path('student_apply_leave/​', StudentViews.student_apply_leave, name="student_apply_leave"),89 path('student_apply_leave_save/​', StudentViews.student_apply_leave_save, name="student_apply_leave_save"),90 path('student_feedback/​', StudentViews.student_feedback, name="student_feedback"),91 path('student_feedback_save/​', StudentViews.student_feedback_save, name="student_feedback_save"),92 path('student_profile/​', StudentViews.student_profile, name="student_profile"),93 path('student_profile_update/​', StudentViews.student_profile_update, name="student_profile_update"),94 path('student_view_result/​', StudentViews.student_view_result, name="student_view_result"),...

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