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27c7158166
Summary: There is a module called `2to3` which you can target for future specifically to remove these, the directory of `caffe2` has the most redundant imports: ```2to3 -f future -w caffe2``` Pull Request resolved: https://github.com/pytorch/pytorch/pull/45033 Reviewed By: seemethere Differential Revision: D23808648 Pulled By: bugra fbshipit-source-id: 38971900f0fe43ab44a9168e57f2307580d36a38
40 lines
1.4 KiB
Python
40 lines
1.4 KiB
Python
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import caffe2.python.hypothesis_test_util as hu
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import hypothesis.strategies as st
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import numpy as np
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from caffe2.python import core, dyndep, workspace
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from hypothesis import given, settings
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dyndep.InitOpsLibrary("//caffe2/caffe2/quantization/server:dnnlowp_ops")
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workspace.GlobalInit(["caffe2", "--caffe2_omp_num_threads=11"])
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class DNNLowPBatchPermutationOpTest(hu.HypothesisTestCase):
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@given(N=st.integers(min_value=1, max_value=100), **hu.gcs_cpu_only)
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@settings(max_examples=10, deadline=None)
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def test_batch_permutation(self, N, gc, dc):
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X = np.round(np.random.rand(N, 10, 20, 3) * 255).astype(np.float32)
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indices = np.arange(N).astype(np.int32)
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np.random.shuffle(indices)
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quantize = core.CreateOperator("Quantize", ["X"], ["X_q"], engine="DNNLOWP")
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batch_perm = core.CreateOperator(
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"BatchPermutation", ["X_q", "indices"], ["Y_q"], engine="DNNLOWP"
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)
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net = core.Net("test_net")
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net.Proto().op.extend([quantize, batch_perm])
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workspace.FeedBlob("X", X)
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workspace.FeedBlob("indices", indices)
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workspace.RunNetOnce(net)
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X_q = workspace.FetchInt8Blob("X_q").data
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Y_q = workspace.FetchInt8Blob("Y_q").data
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def batch_permutation_ref(X, indices):
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return np.array([X[i] for i in indices])
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Y_q_ref = batch_permutation_ref(X_q, indices)
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np.testing.assert_allclose(Y_q, Y_q_ref)
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