pytorch

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## @package ideep_test_util
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# Module caffe2.python.ideep_test_util
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"""
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The IDEEP test utils is a small addition on top of the hypothesis test utils
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under caffe2/python, which allows one to more easily test IDEEP related
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operators.
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"""
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import hypothesis.strategies as st
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from caffe2.proto import caffe2_pb2
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from caffe2.python import hypothesis_test_util as hu
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cpu_do = hu.cpu_do
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ideep_do = caffe2_pb2.DeviceOption(device_type=caffe2_pb2.IDEEP)
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device_options = hu.device_options + ([ideep_do])
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def device_checker_device_options():
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    return st.just(device_options)
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def gradient_checker_device_option():
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    return st.sampled_from(device_options)
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gcs = dict(
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    gc=gradient_checker_device_option(),
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    dc=device_checker_device_options()
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)
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gcs_cpu_only = dict(gc=st.sampled_from([cpu_do]), dc=st.just([cpu_do]))
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gcs_ideep_only = dict(gc=st.sampled_from([ideep_do]), dc=st.just([ideep_do]))
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gcs_cpu_ideep = dict(gc=st.sampled_from([cpu_do, ideep_do]), dc=st.just([cpu_do, ideep_do]))
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