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| import numpy as np |
| import hypothesis.strategies as st |
| import unittest |
| import caffe2.python.hypothesis_test_util as hu |
| from caffe2.python import core, workspace |
| from hypothesis import given |
| import caffe2.python.ideep_test_util as mu |
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| @unittest.skipIf(not workspace.C.use_mkldnn, "No MKLDNN support.") |
| class TestAdamOps(hu.HypothesisTestCase): |
| @given(inputs=hu.tensors(n=4), |
| ITER=st.integers(min_value=0, max_value=10000), |
| LR=st.floats(min_value=0.01, max_value=0.99, |
| allow_nan=False, allow_infinity=False), |
| beta1=st.floats(min_value=0.01, max_value=0.99, |
| allow_nan=False, allow_infinity=False), |
| beta2=st.floats(min_value=0.01, max_value=0.99, |
| allow_nan=False, allow_infinity=False), |
| epsilon=st.floats(min_value=0.01, max_value=0.99, |
| allow_nan=False, allow_infinity=False), |
| **mu.gcs) |
| def test_adam(self, inputs, ITER, LR, beta1, beta2, epsilon, gc, dc): |
| param, mom1, mom2, grad = inputs |
| ITER = np.array([ITER], dtype=np.int64) |
| LR = np.array([LR], dtype=np.float32) |
| mom2 = np.absolute(mom2) |
| op = core.CreateOperator( |
| "Adam", |
| ["param", "mom1", "mom2", "grad", "lr", "iter"], |
| ["output_param", "output_mom1", "output_mom2"], |
| beta1=beta1, beta2=beta2, epsilon=epsilon) |
| |
| input_device_options = {'iter': hu.cpu_do, 'lr': hu.cpu_do} |
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| self.assertDeviceChecks( |
| dc, op, |
| [param, mom1, mom2, grad, LR, ITER], |
| [0], |
| input_device_options=input_device_options, |
| threshold=0.001) |
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| @given(inputs=hu.tensors(n=4), |
| ITER=st.integers(min_value=0, max_value=10000), |
| LR=st.floats(min_value=0.01, max_value=0.99, |
| allow_nan=False, allow_infinity=False), |
| beta1=st.floats(min_value=0.01, max_value=0.99, |
| allow_nan=False, allow_infinity=False), |
| beta2=st.floats(min_value=0.01, max_value=0.99, |
| allow_nan=False, allow_infinity=False), |
| epsilon=st.floats(min_value=0.01, max_value=0.99, |
| allow_nan=False, allow_infinity=False), |
| **mu.gcs) |
| def test_adam_output_grad(self, inputs, ITER, LR, beta1, beta2, epsilon, gc, dc): |
| param, mom1, mom2, grad = inputs |
| ITER = np.array([ITER], dtype=np.int64) |
| LR = np.array([LR], dtype=np.float32) |
| mom2 = np.absolute(mom2) |
|
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| op = core.CreateOperator( |
| "Adam", |
| ["param", "mom1", "mom2", "grad", "lr", "iter"], |
| ["output_param", "output_mom1", "output_mom2", "output_grad"], |
| beta1=beta1, beta2=beta2, epsilon=epsilon) |
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| |
| input_device_options = {'iter': hu.cpu_do, 'lr': hu.cpu_do} |
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| self.assertDeviceChecks( |
| dc, op, |
| [param, mom1, mom2, grad, LR, ITER], |
| [0], |
| input_device_options=input_device_options, |
| threshold=0.001) |
|
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| if __name__ == "__main__": |
| unittest.main() |
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