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  /external/tensorflow/tensorflow/python/kernel_tests/
tensordot_op_test.py 49 math_ops.tensordot(a, b, (a_axes, b_axes))
57 output = math_ops.tensordot(a_ph, b_ph, axes_ph)
71 math_ops.tensordot(a, b, axes_value)
74 math_ops.tensordot(a, b, [[0], [7]])
80 output = math_ops.tensordot(a_ph, b_ph, axes_ph)
98 np_ans = np.tensordot(np_a, np_b, axes_value)
102 tf_ans = math_ops.tensordot(tf_a, tf_b, axes_value).eval()
111 output = math_ops.tensordot(a, b, axes)
115 output = math_ops.tensordot(a, b, axes)
125 output = math_ops.tensordot(a, b, axes
    [all...]
  /external/tensorflow/tensorflow/core/grappler/costs/graph_properties_testdata/
large_graph.pbtxt.html     [all...]
  /external/tensorflow/tensorflow/contrib/signal/python/ops/
mel_ops.py 114 The matrix can be used with @{tf.tensordot} to convert an arbitrary rank
119 M = tf.tensordot(S, A, 1)
120 # tf.tensordot does not support shape inference for this case yet.
mfcc_ops.py 61 mel_spectrograms = tf.tensordot(
  /external/tensorflow/tensorflow/python/ops/linalg/
linalg_impl.py 52 tensordot = math_ops.tensordot variable
  /external/tensorflow/tensorflow/tools/api/golden/
tensorflow.linalg.pbtxt 124 name: "tensordot"
tensorflow.pbtxt     [all...]
  /external/tensorflow/tensorflow/docs_src/api_guides/python/
contrib.signal.md 134 mel_spectrograms = tf.tensordot(
136 # Note: Shape inference for `tf.tensordot` does not currently handle this case.
math_ops.md 114 * @{tf.tensordot}
  /external/tensorflow/tensorflow/contrib/bayesflow/python/ops/
hmc_impl.py 173 loc=tf.tensordot(weights, factors, axes=[[0], [-1]]))
413 loc=tf.tensordot(weights, x, axes=[[0], [-1]]))
655 y = tf.tensordot(x, w, axes=[[1], [0]]) + noise
667 loc=tf.tensordot(x, w, axes=[[1], [0]]))
    [all...]
layers_dense_variational.py 244 # To handle broadcasting, we must use `tensordot`.
245 return standard_ops.tensordot(inputs, kernel, axes=[[-1], [0]])
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  /external/tensorflow/tensorflow/contrib/factorization/python/ops/
kmeans_test.py 327 self.true_score = len(self.points) - np.tensordot(
395 true_score = len(points) - np.tensordot(
  /external/tensorflow/tensorflow/contrib/learn/python/learn/estimators/
kmeans_test.py 335 self.true_score = len(self.points) - np.tensordot(
402 true_score = len(points) - np.tensordot(
  /external/tensorflow/tensorflow/python/layers/
core.py 155 outputs = standard_ops.tensordot(inputs, self.kernel, [[len(shape) - 1],
  /external/tensorflow/tensorflow/python/ops/
math_ops.py 101 @@tensordot
2796 def tensordot(a, b, axes, name=None): function
    [all...]
image_ops_impl.py     [all...]
  /external/tensorflow/tensorflow/contrib/model_pruning/python/layers/
core_layers.py 458 outputs = standard_ops.tensordot(inputs, self.masked_kernel,

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