How to use test_safe method in avocado

Best Python code snippet using avocado_python

problem_unittests.py

Source:problem_unittests.py Github

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1from copy import deepcopy2from unittest import mock3import tensorflow as tf4def test_safe(func):5 """6 Isolate tests7 """8 def func_wrapper(*args):9 with tf.Graph().as_default():10 result = func(*args)11 print('Tests Passed')12 return result13 return func_wrapper14def _assert_tensor_shape(tensor, shape, display_name):15 assert tf.assert_rank(tensor, len(shape), message='{} has wrong rank'.format(display_name))16 tensor_shape = tensor.get_shape().as_list() if len(shape) else []17 wrong_dimension = [ten_dim for ten_dim, cor_dim in zip(tensor_shape, shape)18 if cor_dim is not None and ten_dim != cor_dim]...

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cython_example.py

Source:cython_example.py Github

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...24ctypedef numpy.float64_t DTYPE_t25@cython.boundscheck(False)26@cython.cdivision(True)27@cython.wraparound(False)28def test_safe(double [::1] test, int num_threads):29 cdef int xmax = test.shape[0], ii, jj, mytid30 cdef double[:,:] blergh=numpy.zeros((num_threads,10))31 cdef double[:] blerghsum=numpy.zeros(10)32 with nogil, parallel(num_threads=num_threads):33 mytid = threadid()34 for ii in prange(0,xmax,schedule="static", chunksize=1):35 for jj in range(0,10):36 blergh[mytid,jj] += test[ii]37 return numpy.asarray(blergh).sum(axis=0)38data = numpy.ones(1000000)39%timeit test_unsafe(data,1)40%timeit test_unsafe(data,2)41%timeit test_unsafe(data,4)42%timeit test_unsafe(data,8)43%timeit test_safe(data,1)44%timeit test_safe(data,2)45%timeit test_safe(data,4)46%timeit test_safe(data,8)47testdata=numpy.array([2,3,5,7,11,13,17,19,23,31],dtype="f8")48res = test_safe(testdata,8)49print("We expect ", res)50ii = 051while True or ii<1000000:52 res2 = test_unsafe(testdata,2)53 ii = ii + 154 if numpy.allclose(res,res2):55 continue56 else:57 raise ValueError("WRONG", res2)58%%cython --compile-args=-Ofast --compile-args=-fopenmp --link-args=-fopenmp --link-args=-lgomp59import cython,numpy,os60from cython.parallel cimport prange, parallel, threadid61cimport numpy62DTYPE=numpy.float64...

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