| /external/tensorflow/tensorflow/compiler/tf2xla/kernels/ |
| matrix_set_diag_op.cc | 45 TensorShape batch_shape = input_shape; variable
46 batch_shape.RemoveLastDims(2);
48 TensorShape expected_diag_shape = batch_shape;
71 indicator = builder->Broadcast(indicator, batch_shape.dim_sizes());
|
| matrix_band_part_op.cc | 54 TensorShape batch_shape = input_shape; variable
55 batch_shape.RemoveLastDims(2);
82 indicator = builder->Broadcast(indicator, batch_shape.dim_sizes());
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| /external/tensorflow/tensorflow/core/ops/ |
| linalg_ops.cc | 37 ShapeHandle batch_shape; local
38 TF_RETURN_IF_ERROR(c->Subshape(s, 0, -2, &batch_shape));
39 TF_RETURN_IF_ERROR(c->Concatenate(batch_shape, c->Matrix(d, d), out));
80 // Build final shape (batch_shape + n + k) in <out>.
95 ShapeHandle batch_shape; local
96 TF_RETURN_IF_ERROR(c->Subshape(input, 0, -2, &batch_shape));
98 TF_RETURN_IF_ERROR(c->Concatenate(batch_shape, c->Vector(n), &e_shape));
104 TF_RETURN_IF_ERROR(c->Concatenate(batch_shape, c->Matrix(n, n), &v_shape));
124 ShapeHandle batch_shape; local
125 TF_RETURN_IF_ERROR(c->Subshape(input, 0, -2, &batch_shape));
155 ShapeHandle batch_shape; local
[all...] |
| /external/tensorflow/tensorflow/core/kernels/ |
| linalg_ops_common.cc | 92 TensorShape batch_shape; local
93 AnalyzeInputs(context, &inputs, &input_matrix_shapes, &batch_shape);
97 PrepareOutputs(context, input_matrix_shapes, batch_shape, &outputs,
110 batch_shape.num_elements(), GetCostPerUnit(input_matrix_shapes), shard);
117 TensorShape* batch_shape) {
131 batch_shape->AddDim(in.dim_size(dim));
140 context, in.dim_size(dim) == batch_shape->dim_size(dim),
161 const TensorShape& batch_shape, TensorOutputs* outputs,
193 output_tensor_shape = batch_shape;
|
| /external/tensorflow/tensorflow/python/ops/linalg/ |
| linear_operator.py | 313 def batch_shape(self): member in class:LinearOperator
343 if self.batch_shape.is_fully_defined():
345 self.batch_shape.as_list(), name="batch_shape")
678 `Tensor` with shape `self.batch_shape` and same `dtype` as `self`.
707 `Tensor` with shape `self.batch_shape` and same `dtype` as `self`.
849 if self.batch_shape.is_fully_defined():
850 batch_shape = self.batch_shape
852 batch_shape = self.batch_shape_tensor(
[all...] |
| /external/tensorflow/tensorflow/python/ops/distributions/ |
| distribution.py | 48 "batch_shape",
294 `sample_n_shape = [n] + batch_shape + event_shape`, where `sample_n_shape` is
296 samples, `batch_shape` defines how many independent distributions there are,
298 distributions. Samples are independent along the `batch_shape` dimensions, but
320 # [5, 2, 2], which is [n] + batch_shape + event_shape, where n=5,
321 # batch_shape=[2, 2], and event_shape=[].
572 batch_shape: `Tensor`.
575 if self.batch_shape.is_fully_defined():
576 return ops.convert_to_tensor(self.batch_shape.as_list(),
578 name="batch_shape")
585 def batch_shape(self): member in class:Distribution
[all...] |
