experiments/STT-tensorflow
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Replaced get_shape() to shape.

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This is the recommended method.
This commit is contained in:
Amit Srivastava 2019-03-17 07:51:37 +05:30
parent 76279ff704
commit 991741fe34
1 changed files with 5 additions and 5 deletions
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10
tensorflow/python/keras/utils/kernelized_utils_test.py
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@ -47,7 +47,7 @@ class KernelizedUtilsTest(test.TestCase, parameterized.TestCase):
x = constant_op.constant([0.5, -0.5, -0.5, 0.5])
y = constant_op.constant([0.5, -0.5, -0.5, 0.5])
exact_kernel = exact_kernel_fn(x, y)
shape = exact_kernel.get_shape().as_list()
shape = exact_kernel.shape.as_list()
self.assertLen(shape, 2)
# x and y are identical and therefore K(x, y) will be precisely equal to
# the identity value of the kernel.
@ -61,7 +61,7 @@ class KernelizedUtilsTest(test.TestCase, parameterized.TestCase):
x = constant_op.constant([1.0, 0.4, -2.1, -1.1])
y = constant_op.constant([1.01, 0.39, -2.099, -1.101])
exact_kernel = exact_kernel_fn(x, y)
shape = exact_kernel.get_shape().as_list()
shape = exact_kernel.shape.as_list()
self.assertLen(shape, 2)
# x and y are almost identical and therefore K(x, y) will be almost equal to
# the identity value of the kernel.
@ -75,7 +75,7 @@ class KernelizedUtilsTest(test.TestCase, parameterized.TestCase):
x = constant_op.constant([1.0, 3.4, -2.1, 0.9, 3.3, -2.0], shape=[2, 3])
y = constant_op.constant([1.1, 3.35, -2.05])
exact_kernel = exact_kernel_fn(x, y)
shape = exact_kernel.get_shape().as_list()
shape = exact_kernel.shape.as_list()
self.assertLen(shape, 2)
# The 2 rows of x are close to y. The pairwise kernel values (similarity
# scores) are somewhat close to the identity value of the kernel.
@ -92,7 +92,7 @@ class KernelizedUtilsTest(test.TestCase, parameterized.TestCase):
y = constant_op.constant([1.1, 2.1, -2., 0.9], shape=[2, 2])
exact_kernel = exact_kernel_fn(x, y)
shape = exact_kernel.get_shape().as_list()
shape = exact_kernel.shape.as_list()
self.assertLen(shape, 2)
self.assertAllClose(expected_values, exact_kernel, atol=1e-2)
@ -105,7 +105,7 @@ class KernelizedUtilsTest(test.TestCase, parameterized.TestCase):
x = constant_op.constant([1.0, 3.4, -2.1, -5.1])
y = constant_op.constant([0.5, 2.1, 1.0, 3.0])
exact_kernel = exact_kernel_fn(x, y)
shape = exact_kernel.get_shape().as_list()
shape = exact_kernel.shape.as_list()
self.assertLen(shape, 2)
# x and y are very "far" from each other and so the corresponding kernel
# value will be very low.