Unlock 30% off on Manual Testing Annual Plans this Holiday Season.

Copied to Clipboard!

How to use my_generator method in Slash

Best Python code snippet using slash

stackRNN_tests.py

Source:stackRNN_tests.py

1"""2Unit tests for StackAugmentedRNN class3"""4import sys5sys.path.append('./')6import pytest7import torch8from stackRNN import StackAugmentedRNN9from data import GeneratorData10gen_data_path = './data/logP_labels.csv'11gen_data = GeneratorData(training_data_path=gen_data_path, delimiter=',',12                         cols_to_read=[1], keep_header=False)13hidden_size = 5014stack_width = 5015stack_depth = 1016lr = 0.00117optimizer_instance = torch.optim.Adadelta18use_cuda = True19def test_bidirectional_stack_gru():20    layer_type = 'GRU'21    my_generator = StackAugmentedRNN(input_size=gen_data.n_characters,22                                     hidden_size=hidden_size,23                                     output_size=gen_data.n_characters,24                                     layer_type=layer_type,25                                     n_layers=1, is_bidirectional=True,26                                     has_stack=True,27                                     stack_width=stack_width,28                                     stack_depth=stack_depth,29                                     use_cuda=use_cuda,30                                     optimizer_instance=optimizer_instance,31                                     lr=lr)32    my_generator = my_generator.cuda()33    losses = my_generator.fit(gen_data, 100)34    my_generator.evaluate(gen_data)35def test_unidirectional_stack_gru():36    layer_type = 'GRU'37    my_generator = StackAugmentedRNN(input_size=gen_data.n_characters,38                                     hidden_size=hidden_size,39                                     output_size=gen_data.n_characters,40                                     layer_type=layer_type,41                                     n_layers=1, is_bidirectional=False,42                                     has_stack=True,43                                     stack_width=stack_width,44                                     stack_depth=stack_depth,45                                     use_cuda=use_cuda,46                                     optimizer_instance=optimizer_instance,47                                     lr=lr)48    my_generator = my_generator.cuda()49    losses = my_generator.fit(gen_data, 100)50    my_generator.evaluate(gen_data)51def test_unidirectional_gru_no_stack():52    layer_type = 'GRU'53    my_generator = StackAugmentedRNN(input_size=gen_data.n_characters,54                                     hidden_size=hidden_size,55                                     output_size=gen_data.n_characters,56                                     layer_type=layer_type,57                                     n_layers=1, is_bidirectional=False,58                                     has_stack=False,59                                     stack_width=stack_width,60                                     stack_depth=stack_depth,61                                     use_cuda=use_cuda,62                                     optimizer_instance=optimizer_instance,63                                     lr=lr)64    my_generator = my_generator.cuda()65    losses = my_generator.fit(gen_data, 100)66    my_generator.evaluate(gen_data)67def test_bidirectional_gru_no_stack():68    layer_type = 'GRU'69    my_generator = StackAugmentedRNN(input_size=gen_data.n_characters,70                                     hidden_size=hidden_size,71                                     output_size=gen_data.n_characters,72                                     layer_type=layer_type,73                                     n_layers=1, is_bidirectional=True,74                                     has_stack=False,75                                     stack_width=stack_width,76                                     stack_depth=stack_depth,77                                     use_cuda=use_cuda,78                                     optimizer_instance=optimizer_instance,79                                     lr=lr)80    my_generator = my_generator.cuda()81    losses = my_generator.fit(gen_data, 100)82    my_generator.evaluate(gen_data)83def test_bidirectional_stack_lstm():84    layer_type = 'LSTM'85    my_generator = StackAugmentedRNN(input_size=gen_data.n_characters,86                                     hidden_size=hidden_size,87                                     output_size=gen_data.n_characters,88                                     layer_type=layer_type,89                                     n_layers=1, is_bidirectional=True,90                                     has_stack=True,91                                     stack_width=stack_width,92                                     stack_depth=stack_depth,93                                     use_cuda=use_cuda,94                                     optimizer_instance=optimizer_instance,95                                     lr=lr)96    my_generator = my_generator.cuda()97    losses = my_generator.fit(gen_data, 100)98    my_generator.evaluate(gen_data)99def test_unidirectional_stack_lstm():100    layer_type = 'LSTM'101    my_generator = StackAugmentedRNN(input_size=gen_data.n_characters,102                                     hidden_size=hidden_size,103                                     output_size=gen_data.n_characters,104                                     layer_type=layer_type,105                                     n_layers=1, is_bidirectional=False,106                                     has_stack=True,107                                     stack_width=stack_width,108                                     stack_depth=stack_depth,109                                     use_cuda=use_cuda,110                                     optimizer_instance=optimizer_instance,111                                     lr=lr)112    my_generator = my_generator.cuda()113    losses = my_generator.fit(gen_data, 100)114    my_generator.evaluate(gen_data)115def test_unidirectional_lstm_no_stack():116    layer_type = 'LSTM'117    my_generator = StackAugmentedRNN(input_size=gen_data.n_characters,118                                     hidden_size=hidden_size,119                                     output_size=gen_data.n_characters,120                                     layer_type=layer_type,121                                     n_layers=1, is_bidirectional=False,122                                     has_stack=False,123                                     stack_width=stack_width,124                                     stack_depth=stack_depth,125                                     use_cuda=use_cuda,126                                     optimizer_instance=optimizer_instance,127                                     lr=lr)128    my_generator = my_generator.cuda()129    losses = my_generator.fit(gen_data, 100)130    my_generator.evaluate(gen_data)131def test_bidirectional_lstm_no_stack():132    layer_type = 'LSTM'133    my_generator = StackAugmentedRNN(input_size=gen_data.n_characters,134                                     hidden_size=hidden_size,135                                     output_size=gen_data.n_characters,136                                     layer_type=layer_type,137                                     n_layers=1, is_bidirectional=True,138                                     has_stack=False,139                                     stack_width=stack_width,140                                     stack_depth=stack_depth,141                                     use_cuda=use_cuda,142                                     optimizer_instance=optimizer_instance,143                                     lr=lr)144    my_generator = my_generator.cuda()145    losses = my_generator.fit(gen_data, 100)...

25_generator.py

Source:25_generator.py

1ï»¿# generator2# iterator ë¥¼ ìì±í´ì£¼ë í¨ì3# í¨ìë´ìì yield ëªë ¹ì¼ë¡ ííëë©°, ë³ëë¡ __iter__, __next__, __getitem__ ë±ì í¨ìë¥¼ ë§ë¤ íìê° ìë¤.4# 1. generator5def my_generator():6    yield 07    yield 18    yield 29for i in my_generator():10    print("my_generator :", i)11# generator ê° __iter__ ìëì§ íì¸12print("my_generator :", dir(my_generator()))13print("#"+"-"*20+"#")14# next í¨ì ì¬ì©15def my_generator():16    yield 017    yield 118    yield 219a = my_generator()20print("my_generator next :", next(a))21print("my_generator next :", next(a))22print("my_generator next :", next(a))23print("#"+"-"*20+"#")24# 2. generator ì ìì¸ ê·¸ë¦¬ê³  return25def my_generator():26    yield 027    yield 128    yield 229a = my_generator()30print("my_generator next :", next(a))31print("my_generator next :", next(a))32print("my_generator next :", next(a))33#print("my_generator next :", next(a))   # íìë¥¼ ëì´ê°ë©´ ëì¼íê² StopIteration ë°ì34print("#"+"-"*20+"#")35# return ëªë ¹ì íµí´ ìíë ë©ìì§ ì¶ë ¥ ê°ë¥36def my_generator():37    yield 038    yield 139    yield 240    return "íì ì´ê³¼"  # StopIteration ê³¼ í¨ê» ë©ìì§ ì¶ë ¥41a = my_generator()42print("my_generator next :", next(a))43print("my_generator next :", next(a))44print("my_generator next :", next(a))45# print("my_generator next :", next(a))   # íìë¥¼ ëì´ê°ë©´ ëì¼íê² StopIteration ë°ì46print("#"+"-"*20+"#")47# 3. yield ì í¨ì48def my_generator(a):49    for i in a:50        yield i.upper()51a = ["a", "b", "c"]52for i in my_generator(a):53    print("my_generator :", i)54print("#"+"-"*20+"#")55# 4. yield, from56def my_generator():57    a = [10,20,30]58    for i in a:59        yield i60a = my_generator()61print("my_generator from :", next(a))62print("my_generator from :", next(a))63print("my_generator from :", next(a))...

12_generators_summary.py

Source:12_generators_summary.py

1# summary of generator behaviors (can and cannot do)....2def my_generator():3    values = [1, 2, 3]4    for i in values:5        yield i678# things you cannot do...9# print(my_generator())       # this doesn't behave like a function10# print(my_generator()[0])11# print(len(my_generator()))1213# 4 ways to invoke (work with) a generator...14# 115for i in my_generator():16    print(i)1718# 219results = list(my_generator())20print(results)2122# 323print(*my_generator())2425# 426g = my_generator()27print(g.__next__())28print(next(g))29print(next(g))3031# You can...32if 1 in my_generator():
...

Automation Testing Tutorials

Learn to execute automation testing from scratch with LambdaTest Learning Hub. Right from setting up the prerequisites to run your first automation test, to following best practices and diving deeper into advanced test scenarios. LambdaTest Learning Hubs compile a list of step-by-step guides to help you be proficient with different test automation frameworks i.e. Selenium, Cypress, TestNG etc.