| /external/tensorflow/tensorflow/python/ops/ |
| D | nn_batchnorm_test.py | 340 def _npSuffStats(self, x, axes, shift, keep_dims): argument
343 m_ss = np.sum(x - shift, axis=axis, keepdims=keep_dims)
344 v_ss = np.sum((x - shift) * (x - shift), axis=axis, keepdims=keep_dims)
346 m_ss = np.sum(x, axis=axis, keepdims=keep_dims)
347 v_ss = np.sum(x * x, axis=axis, keepdims=keep_dims)
352 if not keep_dims:
356 def _opSuffStats(self, x, axes, shift, keep_dims): argument
357 return nn_impl.sufficient_statistics(x, axes, shift, keep_dims)
359 def _testSuffStats(self, x_shape, axes, shift, keep_dims, has_shape): argument
361 np_c, np_m, np_v, np_s = self._npSuffStats(x_val, axes, shift, keep_dims)
[all …]
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| D | string_ops.py | 127 keep_dims=False, argument
136 keep_dims=keep_dims,
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| D | math_ops.py | 1326 keep_dims=None): argument
1366 "keep_dims", keep_dims)
1388 keep_dims=None): argument
1429 "keep_dims", keep_dims)
1454 keep_dims=None): argument
1505 "keep_dims", keep_dims)
1526 keep_dims=None): argument
1555 "keep_dims", keep_dims)
1576 keep_dims=None): argument
1605 "keep_dims", keep_dims)
[all …]
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| D | sparse_ops.py | 795 def sparse_reduce_max(sp_input, axis=None, keep_dims=False, argument
837 math_ops._ReductionDims(sp_input, axis, reduction_axes), keep_dims)
843 keep_dims=False, argument
873 math_ops._ReductionDims(sp_input, axis, reduction_axes), keep_dims))
879 def sparse_reduce_sum(sp_input, axis=None, keep_dims=False, argument
921 math_ops._ReductionDims(sp_input, axis, reduction_axes), keep_dims)
927 keep_dims=False, argument
957 math_ops._ReductionDims(sp_input, axis, reduction_axes), keep_dims))
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| D | nn_impl.py | 570 def sufficient_statistics(x, axes, shift=None, keep_dims=False, name=None): argument
614 m_ss = math_ops.reduce_sum(m_ss, axes, keepdims=keep_dims, name="mean_ss")
615 v_ss = math_ops.reduce_sum(v_ss, axes, keepdims=keep_dims, name="var_ss")
657 keep_dims=False): argument
697 if not keep_dims:
708 def weighted_moments(x, axes, frequency_weights, name=None, keep_dims=False): argument
767 if not keep_dims:
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| D | batch_norm_benchmark.py | 84 keep_dims = mode == "py" or mode == "slow"
85 if keep_dims:
99 mean, variance = nn_impl.moments(tensor, axes, keep_dims=keep_dims)
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| /external/tensorflow/tensorflow/python/kernel_tests/ |
| D | reduce_join_op_test.py | 104 keep_dims=False, argument
120 keep_dims=keep_dims,
146 keep_dims=False,
151 keep_dims=True,
159 keep_dims=True,
297 keep_dims=True)
303 keep_dims=True)
309 keep_dims=True, reduction_indices=None)
316 keep_dims=True, reduction_indices=[])
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| D | norm_op_test.py | 72 tf_matrix, ord=ord_, axis=axis_, keep_dims=keep_dims_)
77 tf_matrix, ord=ord_, axis=axis_, keep_dims=keep_dims_)
111 for keep_dims in False, True:
114 keep_dims, use_static_shape)
116 _GetNormOpTest(dtype, shape, ord, axis, keep_dims,
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| /external/tensorflow/tensorflow/contrib/bayesflow/python/ops/ |
| D | monte_carlo_impl.py | 198 axis=0, keep_dims=False, name=None): argument
331 return math_ops.reduce_mean(f(samples), axis=axis, keep_dims=keep_dims)
351 return math_ops.reduce_mean(fx, axis=axis, keep_dims=keep_dims)
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| /external/tensorflow/tensorflow/contrib/lite/kernels/ |
| D | mean_test.cc | 53 std::initializer_list<int> axis, bool keep_dims) { in MeanOpConstModel() argument
58 CreateMeanOptions(builder_, keep_dims).Union()); in MeanOpConstModel()
67 const TensorData& axis, bool keep_dims) { in MeanOpDynamicModel() argument
72 CreateMeanOptions(builder_, keep_dims).Union()); in MeanOpDynamicModel()
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| /external/tensorflow/tensorflow/core/api_def/base_api/ |
| D | api_def_ReduceJoin.pbtxt | 21 set to `1` depending on `keep_dims`.
25 name: "keep_dims"
51 tf.reduce_join(a, 0, keep_dims=True) ==> [["ac", "bd"]]
52 tf.reduce_join(a, 1, keep_dims=True) ==> [["ab"], ["cd"]]
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| D | api_def_Any.pbtxt | 30 name: "keep_dims"
38 `keep_dims` is true, the rank of the tensor is reduced by 1 for each entry in
39 `reduction_indices`. If `keep_dims` is true, the reduced dimensions are
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| D | api_def_Min.pbtxt | 30 name: "keep_dims"
38 `keep_dims` is true, the rank of the tensor is reduced by 1 for each entry in
39 `reduction_indices`. If `keep_dims` is true, the reduced dimensions are
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| D | api_def_All.pbtxt | 30 name: "keep_dims"
38 `keep_dims` is true, the rank of the tensor is reduced by 1 for each entry in
39 `reduction_indices`. If `keep_dims` is true, the reduced dimensions are
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| D | api_def_Max.pbtxt | 30 name: "keep_dims"
38 `keep_dims` is true, the rank of the tensor is reduced by 1 for each entry in
39 `reduction_indices`. If `keep_dims` is true, the reduced dimensions are
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| D | api_def_Prod.pbtxt | 30 name: "keep_dims"
38 `keep_dims` is true, the rank of the tensor is reduced by 1 for each entry in
39 `reduction_indices`. If `keep_dims` is true, the reduced dimensions are
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| D | api_def_Sum.pbtxt | 30 name: "keep_dims"
38 `keep_dims` is true, the rank of the tensor is reduced by 1 for each entry in
39 `reduction_indices`. If `keep_dims` is true, the reduced dimensions are
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| D | api_def_Mean.pbtxt | 30 name: "keep_dims"
38 `keep_dims` is true, the rank of the tensor is reduced by 1 for each entry in
39 `reduction_indices`. If `keep_dims` is true, the reduced dimensions are
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| D | api_def_SparseReduceMaxSparse.pbtxt | 29 name: "keep_dims"
41 `keep_dims` is true, the rank of the tensor is reduced by 1 for each entry in
42 `reduction_axes`. If `keep_dims` is true, the reduced dimensions are retained
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| D | api_def_SparseReduceSumSparse.pbtxt | 29 name: "keep_dims"
41 `keep_dims` is true, the rank of the tensor is reduced by 1 for each entry in
42 `reduction_axes`. If `keep_dims` is true, the reduced dimensions are retained
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| D | api_def_SparseReduceMax.pbtxt | 35 name: "keep_dims"
47 `keep_dims` is true, the rank of the tensor is reduced by 1 for each entry in
48 `reduction_axes`. If `keep_dims` is true, the reduced dimensions are retained
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| D | api_def_SparseReduceSum.pbtxt | 35 name: "keep_dims"
47 `keep_dims` is true, the rank of the tensor is reduced by 1 for each entry in
48 `reduction_axes`. If `keep_dims` is true, the reduced dimensions are retained
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| /external/tensorflow/tensorflow/contrib/factorization/python/ops/ |
| D | gmm_ops.py | 57 x -= math_ops.reduce_mean(x, 0, keep_dims=True)
60 math_ops.square(x), 0, keep_dims=True) / (num_points - 1)
316 math_ops.log(self._covs + 1e-3), 1, keep_dims=True)
354 self._probs[shard_id], axis=1, keep_dims=True)
378 self._w[shard_id], 0, keep_dims=True)
457 math_ops.reduce_logsumexp(op, axis=2, keep_dims=True), axis=0)
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| /external/tensorflow/tensorflow/contrib/gan/python/features/python/ |
| D | virtual_batchnorm_impl.py | 67 shift = array_ops.stop_gradient(math_ops.reduce_mean(y, axes, keep_dims=True))
69 shifted_mean = math_ops.reduce_mean(y - shift, axes, keep_dims=True)
71 mean_squared = math_ops.reduce_mean(math_ops.square(y), axes, keep_dims=True)
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| /external/tensorflow/tensorflow/core/kernels/ |
| D | reduction_ops_common.cc | 78 const bool keep_dims) { in Simplify() argument
92 } else if (keep_dims) { in Simplify()
|