| /external/tensorflow/tensorflow/python/kernel_tests/ |
| D | reduction_ops_test.py | 120 def _tf_reduce(self, x, reduction_axes, keepdims): argument
123 def _np_reduce(self, x, reduction_axes, keepdims): argument
138 def _compare(self, x, reduction_axes, keepdims, feed_dict=None): argument
139 np_ans = self._np_reduce(x, reduction_axes, keepdims)
141 tf_ans = self._tf_reduce(x, reduction_axes, keepdims)
146 def _compareAll(self, x, reduction_axes, feed_dict=None): argument
147 if reduction_axes is not None and np.shape(reduction_axes) == (1,):
149 self._compareAll(x, reduction_axes[0])
150 self._compare(x, reduction_axes, keepdims=False, feed_dict=feed_dict)
151 self._compare(x, reduction_axes, keepdims=True, feed_dict=feed_dict)
[all …]
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| D | reduction_ops_test_big.py | 32 def _tf_reduce(self, x, reduction_axes, keepdims): argument
39 def _tf_reduce_max(self, x, reduction_axes, keepdims): argument
40 return math_ops.reduce_max(x, reduction_axes, keepdims)
42 def _tf_reduce_all(self, x, reduction_axes, keepdims): argument
43 return math_ops.reduce_all(x, reduction_axes, keepdims)
45 def _tf_reduce_mean(self, x, reduction_axes, keepdims): argument
46 return math_ops.reduce_mean(x, reduction_axes, keepdims)
48 def _tf_reduce_sum(self, x, reduction_axes, keepdims): argument
49 return math_ops.reduce_sum(x, reduction_axes, keepdims)
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| D | sparse_ops_test.py | 614 def _compare(self, sp_t, reduction_axes, ndims, keep_dims, do_sum): argument
618 if reduction_axes is None:
624 if not isinstance(reduction_axes, list): # Single scalar.
625 reduction_axes = [reduction_axes]
626 reduction_axes = np.array(reduction_axes).astype(np.int32)
628 reduction_axes = (reduction_axes + ndims) % ndims
630 reduction_axes.sort()
631 for ra in reduction_axes.ravel()[::-1]:
639 tf_dense_ans = sparse_ops.sparse_reduce_sum(sp_t, reduction_axes,
642 tf_dense_ans = sparse_ops.sparse_reduce_max(sp_t, reduction_axes,
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| /external/tensorflow/tensorflow/core/kernels/ |
| D | reduction_ops.h | 56 const ReductionAxes& reduction_axes, const Reducer& reducer) {
57 out.device(d) = in.reduce(reduction_axes, reducer);
66 const ReductionAxes& reduction_axes,
70 out.device(d) = in.reduce(reduction_axes, sum_reducer) /
83 const ReductionAxes& reduction_axes, \
89 reduction_axes, sum_reducer) / \
110 const ReductionAxes& reduction_axes,
115 (in * in.conjugate()).reduce(reduction_axes, sum_reducer).sqrt();
124 const ReductionAxes& reduction_axes,
130 .reduce(reduction_axes, sum_reducer)
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| D | reduction_gpu_kernels.cu.h | 1075 const ReductionAxes& reduction_axes, Op op) {
1082 reduction_axes[0] == 1) { // row reduction
1085 reduction_axes[0] == 0) { // column reduction
1087 } else if (in_rank == 3 && out_rank == 2 && reduction_axes[0] == 1) {
1096 } else if (in_rank == 3 && out_rank == 1 && reduction_axes[0] == 0 &&
1097 reduction_axes[1] == 2) {
1104 if (out_rank == 1) ss << " " << reduction_axes[0];
1105 if (out_rank == 2) ss << " " << reduction_axes[1];
1114 const ReductionAxes& reduction_axes,
1122 const ReductionAxes& reduction_axes,
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| D | sparse_reduce_op.cc | 59 std::vector<int32> reduction_axes(axes_slice.begin(), axes_slice.end()); in SparseTensorReduceHelper() local
61 for (int64 i = 0; i < reduction_axes.size(); ++i) { in SparseTensorReduceHelper()
62 reduction_axes[i] = (reduction_axes[i] + ndims) % ndims; in SparseTensorReduceHelper()
64 std::sort(reduction_axes.begin(), reduction_axes.end()); in SparseTensorReduceHelper()
74 perm.begin(), perm.end(), reduction_axes.begin(), reduction_axes.end(), in SparseTensorReduceHelper()
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| D | reduction_ops_common_gpu.h | 33 const ReductionAxes& reduction_axes,
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| D | reduction_ops_gpu_bool.cu.cc | 40 const Eigen::array<Index, NUM_AXES>& reduction_axes, \
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| D | reduction_ops_gpu_complex128.cu.cc | 40 const Eigen::array<Index, NUM_AXES>& reduction_axes, \
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| D | reduction_ops_gpu_complex64.cu.cc | 40 const Eigen::array<Index, NUM_AXES>& reduction_axes, \
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| D | reduction_ops_half_prod_max_min.cu.cc | 40 const Eigen::array<Index, NUM_AXES>& reduction_axes, \
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| D | reduction_ops_half_mean_sum.cu.cc | 40 const Eigen::array<Index, NUM_AXES>& reduction_axes, \
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| D | reduction_ops_gpu_float.cu.cc | 40 const Eigen::array<Index, NUM_AXES>& reduction_axes, \
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| /external/tensorflow/tensorflow/core/api_def/base_api/ |
| D | api_def_SparseReduceSumSparse.pbtxt | 23 name: "reduction_axes"
40 Reduces `sp_input` along the dimensions given in `reduction_axes`. Unless
42 `reduction_axes`. If `keep_dims` is true, the reduced dimensions are retained
45 If `reduction_axes` has no entries, all dimensions are reduced, and a tensor
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| D | api_def_SparseReduceMaxSparse.pbtxt | 23 name: "reduction_axes"
40 Reduces `sp_input` along the dimensions given in `reduction_axes`. Unless
42 `reduction_axes`. If `keep_dims` is true, the reduced dimensions are retained
45 If `reduction_axes` has no entries, all dimensions are reduced, and a tensor
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| D | api_def_SparseReduceSum.pbtxt | 23 name: "reduction_axes"
46 Reduces `sp_input` along the dimensions given in `reduction_axes`. Unless
48 `reduction_axes`. If `keep_dims` is true, the reduced dimensions are retained
51 If `reduction_axes` has no entries, all dimensions are reduced, and a tensor
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| D | api_def_SparseReduceMax.pbtxt | 23 name: "reduction_axes"
46 Reduces `sp_input` along the dimensions given in `reduction_axes`. Unless
48 `reduction_axes`. If `keep_dims` is true, the reduced dimensions are retained
51 If `reduction_axes` has no entries, all dimensions are reduced, and a tensor
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| /external/tensorflow/tensorflow/core/ops/compat/ops_history_v1/ |
| D | SparseReduceMax.pbtxt | 16 name: "reduction_axes"
63 name: "reduction_axes"
112 name: "reduction_axes"
162 name: "reduction_axes"
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| D | SparseReduceMaxSparse.pbtxt | 16 name: "reduction_axes"
71 name: "reduction_axes"
128 name: "reduction_axes"
186 name: "reduction_axes"
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| D | SparseReduceSum.pbtxt | 16 name: "reduction_axes"
68 name: "reduction_axes"
122 name: "reduction_axes"
177 name: "reduction_axes"
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| D | SparseReduceSumSparse.pbtxt | 16 name: "reduction_axes"
76 name: "reduction_axes"
138 name: "reduction_axes"
201 name: "reduction_axes"
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| /external/tensorflow/tensorflow/python/ops/ |
| D | sparse_ops.py | 1133 reduction_axes = None
1139 math_ops._ReductionDims(sp_input, axis, reduction_axes), keepdims,
1146 math_ops._ReductionDims(sp_input, axis, reduction_axes), keepdims,
1158 reduction_axes=None, keep_dims=None): argument
1218 math_ops._ReductionDims(sp_input, axis, reduction_axes), keepdims)
1228 reduction_axes=None, argument
1267 math_ops._ReductionDims(sp_input, axis, reduction_axes), keepdims))
1323 reduction_axes = None
1329 math_ops._ReductionDims(sp_input, axis, reduction_axes), keepdims,
1335 math_ops._ReductionDims(sp_input, axis, reduction_axes), keepdims,
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| /external/tensorflow/tensorflow/tools/api/golden/v1/ |
| D | tensorflow.sparse.pbtxt | 69 …argspec: "args=[\'sp_input\', \'axis\', \'keepdims\', \'reduction_axes\', \'keep_dims\'], varargs=…
73 …argspec: "args=[\'sp_input\', \'axis\', \'keepdims\', \'reduction_axes\', \'keep_dims\'], varargs=…
77 …argspec: "args=[\'sp_input\', \'axis\', \'keepdims\', \'reduction_axes\', \'keep_dims\'], varargs=…
81 …argspec: "args=[\'sp_input\', \'axis\', \'keepdims\', \'reduction_axes\', \'keep_dims\'], varargs=…
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| /external/tensorflow/tensorflow/python/keras/layers/preprocessing/ |
| D | normalization.py | 158 reduction_axes = tuple(np.delete(range(values.ndim), self.axis))
159 mean = np.mean(values, axis=reduction_axes, dtype=np.float64)
160 variance = np.var(values, axis=reduction_axes, dtype=np.float64)
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| /external/tensorflow/tensorflow/python/keras/layers/ |
| D | normalization.py | 655 def _calculate_mean_and_var(self, inputs, reduction_axes, keep_dims): argument
656 return nn.moments(inputs, reduction_axes, keep_dims=keep_dims)
658 def _moments(self, inputs, reduction_axes, keep_dims): argument
659 mean, variance = self._calculate_mean_and_var(inputs, reduction_axes,
709 reduction_axes = [i for i in range(ndims) if i not in self.axis]
711 del reduction_axes[1] # Do not reduce along virtual batch dim
719 reduction_axes != list(range(ndims - 1))):
754 reduction_axes,
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