| /external/tensorflow/tensorflow/compiler/tf2xla/kernels/ |
| bias_ops.cc | 106 std::vector<int64> reduce_dims(out_backprop_shape.dims() - 1);
107 std::iota(reduce_dims.begin(), reduce_dims.begin() + feature_dim, 0);
108 std::iota(reduce_dims.begin() + feature_dim, reduce_dims.end(),
117 *ctx->GetOrCreateAdd(accumulation_type), reduce_dims);
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| /external/tensorflow/tensorflow/contrib/quantize/python/ |
| quant_ops.py | 134 reduce_dims = [0]
136 reduce_dims = [0, 1, 2]
141 inputs, axis=reduce_dims, name='BatchMin')
150 inputs, axis=reduce_dims, name='BatchMax')
259 reduce_dims = [0]
261 reduce_dims = [0, 1, 2]
266 inputs, axis=reduce_dims, name='BatchMin')
275 inputs, axis=reduce_dims, name='BatchMax')
|
| /external/eigen/unsupported/test/ |
| cxx11_tensor_argmax.cpp | 73 array<DenseIndex, 3> reduce_dims; local
74 for (int d = 0; d < 3; ++d) reduce_dims[d] = d;
77 reduce_dims, internal::ArgMaxTupleReducer<Tuple<DenseIndex, float> >());
79 Tensor<float, 1, DataLayout> max_by_dims = tensor.maximum(reduce_dims);
105 array<DenseIndex, 3> reduce_dims; local
106 for (int d = 0; d < 3; ++d) reduce_dims[d] = d;
109 reduce_dims, internal::ArgMinTupleReducer<Tuple<DenseIndex, float> >());
111 Tensor<float, 1, DataLayout> min_by_dims = tensor.minimum(reduce_dims);
|
| /external/tensorflow/tensorflow/compiler/xla/tests/ |
| batch_normalization_test.cc | 466 std::vector<int64> reduce_dims; local
469 reduce_dims.push_back(i);
474 ReferenceUtil::Reduce4DTo1D(input_array, /*init=*/0.0f, reduce_dims,
478 ReferenceUtil::Reduce4DTo1D(*input_squared, /*init=*/0.0f, reduce_dims,
567 std::vector<int64> reduce_dims; local
570 reduce_dims.push_back(i);
575 ReferenceUtil::Reduce4DTo1D(input_array, /*init=*/0.0f, reduce_dims,
579 ReferenceUtil::Reduce4DTo1D(*input_squared, /*init=*/0.0f, reduce_dims,
678 std::vector<int64> reduce_dims; local
681 reduce_dims.push_back(i)
[all...] |
| reduce_test.cc | 549 std::vector<int64> reduce_dims; member in struct:xla::__anon44647::BoundsLayout
554 spec.bounds.size() - spec.reduce_dims.size(),
557 absl::StrJoin(spec.reduce_dims, ""));
[all...] |
| /external/tensorflow/tensorflow/core/kernels/ |
| bincount_op.cc | 81 Eigen::array<int, 1> reduce_dims({0});
82 output.device(context->eigen_cpu_device()) = partial_bins.sum(reduce_dims);
|
| fused_batch_norm_op.cc | 99 Eigen::array<int, 1> reduce_dims({0});
104 Eigen::IndexList<Eigen::type2index<0> > reduce_dims; local
119 mean.device(d) = (x_rest_by_depth.sum(reduce_dims) * rest_size_inv);
130 variance.device(d) = x_centered.square().sum(reduce_dims) * rest_size_inv;
191 Eigen::array<int, 1> reduce_dims({0});
196 Eigen::IndexList<Eigen::type2index<0> > reduce_dims; local
215 (y_backprop_rest_by_depth * x_scaled).sum(reduce_dims);
216 auto y_backprop_sum = y_backprop_rest_by_depth.sum(reduce_dims);
230 (y_backprop_rest_by_depth * x_centered).mean(reduce_dims))
[all...] |
| /external/eigen/unsupported/Eigen/CXX11/src/Tensor/ |
| TensorArgMax.h | 176 const Dims& reduce_dims)
177 : m_xpr(expr), m_reduce_op(reduce_op), m_return_dim(return_dim), m_reduce_dims(reduce_dims) {}
187 const Dims& reduce_dims() const { return m_reduce_dims; } function in class:Eigen::TensorTupleReducerOp
224 m_impl(op.expression().index_tuples().reduce(op.reduce_dims(), op.reduce_op()), device),
|
| /external/tensorflow/tensorflow/contrib/distributions/python/ops/ |
| independent.py | 317 reduce_dims = [-i - 1 for i in range(0, num_reduce_dims)]
320 kullback_leibler.kl_divergence(p, q, name=name), axis=reduce_dims)
334 reduce_dims = math_ops.range(-num_reduce_dims - 1, -1, 1)
336 kullback_leibler.kl_divergence(p, q, name=name), axis=reduce_dims)
|
| /external/tensorflow/tensorflow/compiler/xla/service/ |
| algebraic_simplifier.cc | [all...] |
| /external/tensorflow/tensorflow/core/grappler/optimizers/ |
| constant_folding.cc | 622 BCast::Vec reduce_dims[2]; local
623 reduce_dims[0] = bcast.grad_x_reduce_idx();
624 reduce_dims[1] = bcast.grad_y_reduce_idx();
630 int reduction_indices = reduce_dims[j].size();
634 value.vec<int32>()(i) = reduce_dims[j][i];
636 value.vec<int64>()(i) = reduce_dims[j][i];
[all...] |
