def testToTensorValueFromTFV1SparseTensorValue(self):
original = tf.compat.v1.SparseTensorValue(
values=np.array([0.5, -1., 0.5, -1.]),
indices=np.array([[0, 3, 1], [0, 20, 0], [1, 3, 1], [1, 20, 0]]),
dense_shape=np.array([2, 100, 3]))
sparse_value = util.to_tensor_value(original)
self.assertAllClose(sparse_value.values, original.values)
self.assertAllClose(sparse_value.indices, original.indices)
self.assertAllClose(sparse_value.dense_shape, original.dense_shape)
def testToTensorValueFromTFSparseTensor(self):
original = tf.SparseTensor(values=[0.5, -1., 0.5, -1.],
indices=[[0, 3, 1], [0, 20, 0], [1, 3, 1],
[1, 20, 0]],
dense_shape=[2, 100, 3])
sparse_value = util.to_tensor_value(original)
self.assertAllClose(sparse_value.values, original.values.numpy())
self.assertAllClose(sparse_value.indices, original.indices.numpy())
self.assertAllClose(sparse_value.dense_shape,
original.dense_shape.numpy())
def testToTensorValueFromTFRaggedTensorUsingRowLengths(self):
original = tf.RaggedTensor.from_nested_row_lengths(
[3, 1, 4, 1, 5, 9, 2, 7, 1, 8, 8, 2, 1],
[[3, 3], [2, 1, 1, 1, 0, 3], [2, 1, 0, 3, 3, 1, 1, 2]])
ragged_value = util.to_tensor_value(original)
self.assertAllClose(ragged_value.values, original.flat_values.numpy())
self.assertLen(ragged_value.nested_row_splits, 3)
original_nested_row_splits = original.nested_row_splits
self.assertAllClose(ragged_value.nested_row_splits[0],
original_nested_row_splits[0].numpy())
self.assertAllClose(ragged_value.nested_row_splits[1],
original_nested_row_splits[1].numpy())
self.assertAllClose(ragged_value.nested_row_splits[2],
original_nested_row_splits[2].numpy())
def testToTensorValueFromTFRaggedTensor(self):
original = tf.RaggedTensor.from_nested_row_splits(
[3, 1, 4, 1, 5, 9, 2, 7, 1, 8, 8, 2, 1],
[[0, 3, 6], [0, 2, 3, 4, 5, 5, 8], [0, 2, 3, 3, 6, 9, 10, 11, 13]])
ragged_value = util.to_tensor_value(original)
self.assertAllClose(ragged_value.values, original.flat_values.numpy())
self.assertLen(ragged_value.nested_row_splits, 3)
original_nested_row_splits = original.nested_row_splits
self.assertAllClose(ragged_value.nested_row_splits[0],
original_nested_row_splits[0].numpy())
self.assertAllClose(ragged_value.nested_row_splits[1],
original_nested_row_splits[1].numpy())
self.assertAllClose(ragged_value.nested_row_splits[2],
original_nested_row_splits[2].numpy())
def testToTensorValueFromTFV1RaggedTensorValue(self):
ragged_value = util.to_tensor_value(
tf.compat.v1.ragged.RaggedTensorValue(
values=tf.compat.v1.ragged.RaggedTensorValue(
values=tf.compat.v1.ragged.RaggedTensorValue(
values=np.array(
[3, 1, 4, 1, 5, 9, 2, 7, 1, 8, 8, 2, 1]),
row_splits=np.array([0, 2, 3, 3, 6, 9, 10, 11, 13])),
row_splits=np.array([0, 2, 3, 4, 5, 5, 8])),
row_splits=np.array([0, 3, 6])))
self.assertAllClose(ragged_value.values,
np.array([3, 1, 4, 1, 5, 9, 2, 7, 1, 8, 8, 2, 1]))
self.assertLen(ragged_value.nested_row_splits, 3)
self.assertAllClose(ragged_value.nested_row_splits[0],
np.array([0, 3, 6]))
self.assertAllClose(ragged_value.nested_row_splits[1],
np.array([0, 2, 3, 4, 5, 5, 8]))
self.assertAllClose(ragged_value.nested_row_splits[2],
np.array([0, 2, 3, 3, 6, 9, 10, 11, 13]))
def testToTensorValueFromNumpy(self):
self.assertAllClose(util.to_tensor_value([1, 2, 3]),
np.array([1, 2, 3]))
self.assertAllClose(util.to_tensor_value(np.array([1, 2, 3])),
np.array([1, 2, 3]))
def testToTensorValueFromTFTensor(self):
self.assertAllClose(util.to_tensor_value(tf.constant([1, 2, 3])),
np.array([1, 2, 3]))
