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removing base_module for glow/glow/torch_glow/tests:test_utils
Differential Revision: D55695991
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torch_glow/tests/backends/NNPI/model_serialization_test.py

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import torch
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import torch.jit
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import torch_glow
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from tests import utils
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from glow.glow.torch_glow.tests.tests import utils
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class Bar(torch.nn.Module):

torch_glow/tests/backends/NNPI/qconv_big_stride_small_kernel_test.py

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import unittest
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import torch
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from tests import utils
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from glow.glow.torch_glow.tests.tests import utils
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class TestQuantizedConv2dBigStrideSmallKernel(utils.TorchGlowTestCase):

torch_glow/tests/functionality/blocklist_test.py

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import torch
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import torch_glow
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from tests import utils
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from glow.glow.torch_glow.tests.tests import utils
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from tests.utils import GLOW_FUSION_GROUP, SUBGRAPH_ATTR
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torch_glow/tests/functionality/compilation_spec_test.py

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import torch
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import torch_glow
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from tests import utils
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from glow.glow.torch_glow.tests.tests import utils
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class TestCompilationSpec(utils.TorchGlowTestCase):

torch_glow/tests/functionality/conv_to_glow_test.py

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import torch
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import torch_glow
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from tests import utils
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from glow.glow.torch_glow.tests.tests import utils
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def create_model(x, relu, bias=True):

torch_glow/tests/functionality/fuse_parallel_branches_test.py

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import torch
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import torch_glow
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from tests import utils
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from glow.glow.torch_glow.tests.tests import utils
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class TestFuseParallelBranches(utils.TorchGlowTestCase):

torch_glow/tests/functionality/fused_linear_test.py

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import torch
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import torch_glow
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from tests import utils
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from glow.glow.torch_glow.tests.tests import utils
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from tests.utils import graph_contains_str
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torch_glow/tests/functionality/input_spec_test.py

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import torch
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import torch_glow
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from tests import utils
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from glow.glow.torch_glow.tests.tests import utils
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def get_compilation_spec(inputs):

torch_glow/tests/functionality/jit_vs_glow_path_test.py

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import torch
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import torch.nn.functional as F
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import torch_glow
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from tests import utils
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from glow.glow.torch_glow.tests.tests import utils
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class TestJITVsGlowPath(utils.TorchGlowTestCase):

torch_glow/tests/functionality/load_backend_specific_options_test.py

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import torch
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import torch_glow
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from tests import utils
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from glow.glow.torch_glow.tests.tests import utils
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class TestLoadBackendSpecificOptions(utils.TorchGlowTestCase):

torch_glow/tests/functionality/max_fusion_merge_size_test.py

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import torch
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import torch_glow
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from tests import utils
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from glow.glow.torch_glow.tests.tests import utils
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from tests.utils import GLOW_FUSION_GROUP
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torch_glow/tests/functionality/min_graph_size_test.py

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import torch
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import torch_glow
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from tests import utils
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from glow.glow.torch_glow.tests.tests import utils
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from tests.utils import GLOW_FUSION_GROUP
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torch_glow/tests/functionality/only_tensor_outputs_test.py

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import torch
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import torch_glow
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from tests import utils
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from glow.glow.torch_glow.tests.tests import utils
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from tests.utils import GLOW_FUSION_GROUP
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torch_glow/tests/functionality/print_jit_index_test.py

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import torch
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import torch_glow
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from tests import utils
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from glow.glow.torch_glow.tests.tests import utils
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class TestPrintJitNodeIndices(utils.TorchGlowTestCase):

torch_glow/tests/functionality/quantized_cut_in_the_middle_test.py

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import torch
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import torch_glow
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from tests import utils
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from glow.glow.torch_glow.tests.tests import utils
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from tests.utils import GLOW_FUSION_GROUP
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torch_glow/tests/functionality/randomize_constants_test.py

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import torch
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import torch_glow
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from tests import utils
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from glow.glow.torch_glow.tests.tests import utils
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class Model(torch.nn.Module):

torch_glow/tests/functionality/remove_exceptions_test.py

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import torch
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import torch_glow
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from tests import utils
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from glow.glow.torch_glow.tests.tests import utils
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from tests.utils import graph_contains_str
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torch_glow/tests/functionality/set_glow_backend_test.py

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from __future__ import absolute_import, division, print_function, unicode_literals
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import torch_glow
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from tests import utils
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from glow.glow.torch_glow.tests.tests import utils
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class TestSetGlowBackend(utils.TorchGlowTestCase):

torch_glow/tests/functionality/shape_inference_test.py

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import torch
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import torch_glow
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from tests import utils
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from glow.glow.torch_glow.tests.tests import utils
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class TestGlowShapeInference(utils.TorchGlowTestCase):

torch_glow/tests/functionality/to_glow_multiple_input_sets_test.py

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import torch
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import torch_glow
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from tests import utils
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from glow.glow.torch_glow.tests.tests import utils
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class Foo(torch.nn.Module):

torch_glow/tests/functionality/to_glow_num_devices_to_use_test.py

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import torch
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import torch_glow
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from tests import utils
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from glow.glow.torch_glow.tests.tests import utils
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class SimpleModule(torch.nn.Module):

torch_glow/tests/functionality/to_glow_save_preprocessed_test.py

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import torch
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import torch.jit
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import torch_glow
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from tests import utils
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from glow.glow.torch_glow.tests.tests import utils
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# Use a model containing quantized::conv2d to verify preprocessed module is

torch_glow/tests/functionality/to_glow_selective_test.py

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import torch
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import torch_glow
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from tests import utils
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from glow.glow.torch_glow.tests.tests import utils
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class Qux(torch.nn.Module):

torch_glow/tests/functionality/to_glow_tuple_output_test.py

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import torch
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import torch_glow
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from tests import utils
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from glow.glow.torch_glow.tests.tests import utils
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from tests.utils import assertModulesEqual
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torch_glow/tests/functionality/to_glow_write_to_onnx_test.py

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import torch
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import torch_glow
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from tests import utils
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from glow.glow.torch_glow.tests.tests import utils
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class Foo(torch.nn.Module):

torch_glow/tests/nodes/Int_test.py

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from __future__ import absolute_import, division, print_function, unicode_literals
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import torch
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from tests import utils
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from glow.glow.torch_glow.tests.tests import utils
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class SimpleIntModule(torch.nn.Module):

torch_glow/tests/nodes/abs_test.py

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from __future__ import absolute_import, division, print_function, unicode_literals
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import torch
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from tests import utils
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from glow.glow.torch_glow.tests.tests import utils
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class SimpleAbsModule(torch.nn.Module):

torch_glow/tests/nodes/adaptive_avg_pool2d_test.py

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import torch
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import torch.nn.functional as F
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from tests import utils
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from glow.glow.torch_glow.tests.tests import utils
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class SimpleAdapativeAvgPool2dModule(torch.nn.Module):

torch_glow/tests/nodes/add_test.py

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from __future__ import absolute_import, division, print_function, unicode_literals
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import torch
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from tests import utils
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from glow.glow.torch_glow.tests.tests import utils
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class SimpleAddModule(torch.nn.Module):

torch_glow/tests/nodes/addmm_test.py

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from __future__ import absolute_import, division, print_function, unicode_literals
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import torch
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from tests import utils
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from glow.glow.torch_glow.tests.tests import utils
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class SimpleAddMmModule(torch.nn.Module):

torch_glow/tests/nodes/and_test.py

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from __future__ import absolute_import, division, print_function, unicode_literals
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import torch
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from tests import utils
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from glow.glow.torch_glow.tests.tests import utils
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class SimpleAndModule(torch.nn.Module):

torch_glow/tests/nodes/arange_test.py

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from __future__ import absolute_import, division, print_function, unicode_literals
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import torch
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from tests import utils
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from glow.glow.torch_glow.tests.tests import utils
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class SimpleArangeModule(torch.nn.Module):

torch_glow/tests/nodes/arg_min_max_test.py

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# pyre-ignore-all-errors
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import torch
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from glow.glow.torch_glow.tests.tests import utils
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class ArgMinModule(torch.nn.Module):

torch_glow/tests/nodes/argsort_test.py

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from __future__ import absolute_import, division, print_function, unicode_literals
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import torch
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from tests import utils
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from glow.glow.torch_glow.tests.tests import utils
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class SimpleArgSortModule(torch.nn.Module):

torch_glow/tests/nodes/attention_test.py

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import torch
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import torch_glow
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from glow.glow.torch_glow.tests.tests import utils
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class SimpleAttentionModule(torch.nn.Module):

torch_glow/tests/nodes/avgpool1d_test.py

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import torch
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import torch.nn.functional as F
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from glow.glow.torch_glow.tests.tests import utils
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class SimpleAvgPool1dModule(torch.nn.Module):

torch_glow/tests/nodes/avgpool2d_test.py

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import torch
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import torch.nn.functional as F
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from tests import utils
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from glow.glow.torch_glow.tests.tests import utils
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class SimpleAvgPool2dModule(torch.nn.Module):

torch_glow/tests/nodes/avgpool3d_test.py

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import torch
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import torch.nn.functional as F
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from glow.glow.torch_glow.tests.tests import utils
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class SimpleAvgPool3dModule(torch.nn.Module):

torch_glow/tests/nodes/baddbmm_test.py

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from __future__ import absolute_import, division, print_function, unicode_literals
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import torch
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from glow.glow.torch_glow.tests.tests import utils
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class SimpleBAddBmmModule(torch.nn.Module):

torch_glow/tests/nodes/batch_permutation_test.py

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from __future__ import absolute_import, division, print_function, unicode_literals
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import torch
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from glow.glow.torch_glow.tests.tests import utils
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class SimpleBatchPermutationModule(torch.nn.Module):

torch_glow/tests/nodes/batchnorm0d_test.py

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import torch
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import torch.nn as nn
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from glow.glow.torch_glow.tests.tests import utils
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class TestBatchNorm0D(utils.TorchGlowTestCase):

torch_glow/tests/nodes/batchnorm1d_test.py

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import torch
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import torch.nn as nn
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from glow.glow.torch_glow.tests.tests import utils
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class TestBatchNorm1D(utils.TorchGlowTestCase):

torch_glow/tests/nodes/batchnorm2d_test.py

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import torch
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import torch.nn as nn
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from glow.glow.torch_glow.tests.tests import utils
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class TestBatchNorm2D(utils.TorchGlowTestCase):

torch_glow/tests/nodes/batchnorm3d_test.py

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import torch
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import torch.nn as nn
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from glow.glow.torch_glow.tests.tests import utils
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class TestBatchNorm3D(utils.TorchGlowTestCase):

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