add tanhshrink_py #1146
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add tanhshrink_py #1146
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| # @parameterized.named_parameters( | ||
| # ("float16", np.float16), ("float32", np.float32), ("float64", np.float64) | ||
| # ) | ||
| # def test_tanhshrink(self, dtype): | ||
| # x = tf.constant([-2.0, -1.0, 0.0, 1.0, 2.0], dtype=dtype) | ||
| # expected_result = tf.constant( | ||
| # [-1.0359724, -0.23840582, 0.0, 0.23840582, 1.0359724], dtype=dtype | ||
| # ) | ||
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| # self.assertAllCloseAccordingToType(tanhshrink(x), expected_result) | ||
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| # @parameterized.named_parameters(("float32", np.float32), ("float64", np.float64)) | ||
| # def test_theoretical_gradients(self, dtype): | ||
| # # Only test theoretical gradients for float32 and float64 | ||
| # # because of the instability of float16 while computing jacobian | ||
| # x = tf.constant([-2.0, -1.0, 0.0, 1.0, 2.0], dtype=dtype) | ||
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| # theoretical, numerical = tf.test.compute_gradient(tanhshrink, [x]) | ||
| # self.assertAllCloseAccordingToType(theoretical, numerical, atol=1e-4) | ||
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Maybe we could actually remove all that? The check with random tensors is much more robust. What do you think?
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Good idea. I remove them later.
jrruijli
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Dec 23, 2020
* add tanhshrink_py * format code * remove useless test cases
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Related #1114