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neilisaac / torch   python

Repository URL to install this package:

Version: 1.8.0 

/ python / operator_test / mean_op_test.py






from caffe2.python import core
import caffe2.python.hypothesis_test_util as hu
import caffe2.python.serialized_test.serialized_test_util as serial
import hypothesis.strategies as st
import numpy as np
import unittest


class TestMean(serial.SerializedTestCase):
    @serial.given(
        k=st.integers(1, 5),
        n=st.integers(1, 10),
        m=st.integers(1, 10),
        in_place=st.booleans(),
        seed=st.integers(0, 2**32 - 1),
        **hu.gcs
    )
    def test_mean(self, k, n, m, in_place, seed, gc, dc):
        np.random.seed(seed)
        input_names = []
        input_vars = []

        for i in range(k):
            X_name = 'X' + str(i)
            input_names.append(X_name)
            var = np.random.randn(n, m).astype(np.float32)
            input_vars.append(var)

        def mean_ref(*args):
            return [np.mean(args, axis=0)]

        op = core.CreateOperator(
            "Mean",
            input_names,
            ['Y' if not in_place else 'X0'],
        )

        self.assertReferenceChecks(
            device_option=gc,
            op=op,
            inputs=input_vars,
            reference=mean_ref,
        )

        self.assertGradientChecks(
            device_option=gc,
            op=op,
            inputs=input_vars,
            outputs_to_check=0,
            outputs_with_grads=[0],
        )

        self.assertDeviceChecks(dc, op, input_vars, [0])


if __name__ == "__main__":
    unittest.main()