/external/tensorflow/tensorflow/lite/testing/nnapi_tflite_zip_tests/ |
D | not_supported.txt | 157 mean/mean_axis=0,const_axis=True,input_dtype=tf.float32,input_shape=[3,3,2,4],keepdims=True 158 mean/mean_axis=0,const_axis=True,input_dtype=tf.float32,input_shape=[3,3,2,4],keepdims=False 159 mean/mean_axis=0,const_axis=False,input_dtype=tf.float32,input_shape=[3,3,2,4],keepdims=True 160 mean/mean_axis=0,const_axis=False,input_dtype=tf.float32,input_shape=[3,3,2,4],keepdims=False 161 mean/mean_axis=0,const_axis=True,input_dtype=tf.int32,input_shape=[3,3,2,4],keepdims=True 162 mean/mean_axis=0,const_axis=True,input_dtype=tf.int32,input_shape=[3,3,2,4],keepdims=False 163 mean/mean_axis=0,const_axis=False,input_dtype=tf.int32,input_shape=[3,3,2,4],keepdims=True 164 mean/mean_axis=0,const_axis=False,input_dtype=tf.int32,input_shape=[3,3,2,4],keepdims=False 165 mean/mean_axis=0,const_axis=True,input_dtype=tf.int64,input_shape=[3,3,2,4],keepdims=True 166 mean/mean_axis=0,const_axis=True,input_dtype=tf.int64,input_shape=[3,3,2,4],keepdims=False [all …]
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/external/tensorflow/tensorflow/python/ops/ragged/ |
D | ragged_boolean_mask_op_test.py | 51 keepdims=False, 57 keepdims=True, 63 keepdims=False, 69 keepdims=True, 75 keepdims=False, 84 keepdims=True, 90 keepdims=True, 96 keepdims=True, 103 keepdims=True, 109 keepdims=False, [all …]
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D | ragged_math_ops.py | 403 keepdims, argument 443 if keepdims: 470 rt_input, axis[-1], keepdims) 472 inner_reduced, axis[:-1], keepdims) 498 rt_input.values, axis - 1, keepdims)) 501 def reduce_sum(input_tensor, axis=None, keepdims=None, name=None): argument 505 axis, keepdims, name or 'RaggedReduceSum') 508 def reduce_prod(input_tensor, axis=None, keepdims=None, name=None): argument 512 axis, keepdims, name or 'RaggedReduceProd') 515 def reduce_min(input_tensor, axis=None, keepdims=None, name=None): argument [all …]
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D | ragged_array_ops.py | 37 def boolean_mask(data, mask, keepdims=False, name=None): argument 162 masked_values = boolean_mask(data, mask, keepdims) 165 if keepdims: 187 masked_values = boolean_mask(data.values, segment_mask, keepdims=False) 197 return boolean_mask(data, mask, keepdims) 204 if mask.shape.ndims >= 2 and keepdims: 215 if mask.shape.ndims > 2 and keepdims:
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/external/tensorflow/tensorflow/python/ops/ |
D | math_ops.py | 1304 def _may_reduce_to_scalar(keepdims, axis, output): argument 1306 if not common_shapes.has_fully_defined_shape(output) and (not keepdims) and ( 1317 keepdims=None, argument 1362 keepdims = deprecation.deprecated_argument_lookup("keepdims", keepdims, 1364 return reduce_sum(input_tensor, axis, keepdims, name) 1369 def reduce_sum(input_tensor, axis=None, keepdims=False, name=None): argument 1407 keepdims = False if keepdims is None else keepdims 1409 keepdims, axis, 1411 input_tensor, _ReductionDims(input_tensor, axis), keepdims, 1416 def reduce_euclidean_norm(input_tensor, axis=None, keepdims=False, name=None): argument [all …]
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D | linalg_ops.py | 430 keepdims=None, argument 492 keepdims=keepdims, 503 keepdims=None, argument 564 keepdims = deprecation.deprecated_argument_lookup('keepdims', keepdims, 566 if keepdims is None: 567 keepdims = False 615 keepdims=True), 621 tensor * math_ops.conj(tensor), axis, keepdims=True)) 628 result = math_ops.reduce_sum(result, sum_axis, keepdims=True) 630 result = math_ops.reduce_max(result, axis[-1], keepdims=True) [all …]
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D | sparse_ops.py | 1022 sp_input, axis=None, keepdims=None, output_is_sparse=False, name=None): argument 1078 if keepdims is None: 1079 keepdims = False 1088 math_ops._ReductionDims(sp_input, axis, reduction_axes), keepdims, 1095 math_ops._ReductionDims(sp_input, axis, reduction_axes), keepdims, 1106 def sparse_reduce_max(sp_input, axis=None, keepdims=None, argument 1160 keepdims = deprecation.deprecated_argument_lookup("keepdims", keepdims, 1162 if keepdims is None: 1163 keepdims = False 1167 math_ops._ReductionDims(sp_input, axis, reduction_axes), keepdims) [all …]
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D | nn_impl.py | 435 square_sum = math_ops.reduce_sum(math_ops.square(x), axis, keepdims=True) 812 keepdims=None): argument 839 "keepdims", keepdims, "keep_dims", keep_dims) 861 m_ss = math_ops.reduce_sum(m_ss, axes, keepdims=keep_dims, name="mean_ss") 862 v_ss = math_ops.reduce_sum(v_ss, axes, keepdims=keep_dims, name="var_ss") 867 def sufficient_statistics_v2(x, axes, shift=None, keepdims=False, name=None): argument 892 x=x, axes=axes, shift=shift, keep_dims=keepdims, name=name) 934 keepdims=None): argument 963 "keepdims", keepdims, "keep_dims", keep_dims) 972 mean = math_ops.reduce_mean(y, axes, keepdims=True, name="mean") [all …]
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D | nn_grad.py | 295 sum_channels = math_ops.reduce_sum(grad_softmax * softmax, -1, keepdims=True) 314 return grad - math_ops.reduce_sum(grad, -1, keepdims=True) * softmax 943 keepdims = False 946 keepdims = True 950 mean_grad_y = math_ops.reduce_mean(grad_y, reduce_axis, keepdims=keepdims) 951 mean_x = math_ops.reduce_mean(x, reduce_axis, keepdims=keepdims) 955 keepdims=keepdims) 959 grad_y * x_offset, axis=reduce_axis, keepdims=keepdims) 963 grad_y * x_offset, axis=reduce_axis, keepdims=keepdims)
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D | string_ops.py | 334 keepdims=None): argument 336 "keepdims", keepdims, "keep_dims", keep_dims) 352 keepdims=False, argument 356 inputs, axis, keep_dims=keepdims, separator=separator, name=name)
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/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) 150 self._compare(x, reduction_axes, keepdims=False, feed_dict=feed_dict) 151 self._compare(x, reduction_axes, keepdims=True, feed_dict=feed_dict) 181 def _tf_reduce(self, x, reduction_axes, keepdims): argument 182 return math_ops.reduce_sum(x, reduction_axes, keepdims) 184 def _np_reduce(self, x, reduction_axes, keepdims): argument [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 | norm_op_test.py | 70 np_norm = np.linalg.norm(matrix, ord=ord_, axis=axis_, keepdims=keep_dims_) 75 tf_matrix, ord=ord_, axis=axis_, keepdims=keep_dims_) 80 tf_matrix, ord=ord_, axis=axis_, keepdims=keep_dims_)
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/external/tensorflow/tensorflow/contrib/losses/python/metric_learning/ |
D | metric_loss_ops.py | 53 math_ops.reduce_sum(math_ops.square(feature), axis=[1], keepdims=True), 57 keepdims=True)) - 2.0 * math_ops.matmul(feature, 134 axis_minimums = math_ops.reduce_min(data, dim, keepdims=True) 137 keepdims=True) + axis_minimums 153 axis_maximums = math_ops.reduce_max(data, dim, keepdims=True) 156 keepdims=True) + axis_maximums 204 math_ops.cast(mask, dtype=dtypes.float32), 1, keepdims=True), 291 labels_remapped /= math_ops.reduce_sum(labels_remapped, 1, keepdims=True) 397 labels_remapped /= math_ops.reduce_sum(labels_remapped, 1, keepdims=True) 450 row_minimums = math_ops.reduce_min(diff, 1, keepdims=True) [all …]
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/external/tensorflow/tensorflow/contrib/distributions/python/kernel_tests/bijectors/ |
D | batch_normalization_test.py | 112 keepdims = len(event_dims) > 1 115 x_, axis=reduction_axes, keepdims=keepdims) 116 expected_batch_var = np.var(x_, axis=reduction_axes, keepdims=keepdims)
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/external/tensorflow/tensorflow/tools/api/golden/v2/ |
D | tensorflow.math.pbtxt | 105 …argspec: "args=[\'input\', \'axis\', \'keepdims\', \'dtype\', \'name\'], varargs=None, keywords=No… 305 …argspec: "args=[\'input_tensor\', \'axis\', \'keepdims\', \'name\'], varargs=None, keywords=None, … 309 …argspec: "args=[\'input_tensor\', \'axis\', \'keepdims\', \'name\'], varargs=None, keywords=None, … 313 …argspec: "args=[\'input_tensor\', \'axis\', \'keepdims\', \'name\'], varargs=None, keywords=None, … 317 …argspec: "args=[\'input_tensor\', \'axis\', \'keepdims\', \'name\'], varargs=None, keywords=None, … 321 …argspec: "args=[\'input_tensor\', \'axis\', \'keepdims\', \'name\'], varargs=None, keywords=None, … 325 …argspec: "args=[\'input_tensor\', \'axis\', \'keepdims\', \'name\'], varargs=None, keywords=None, … 329 …argspec: "args=[\'input_tensor\', \'axis\', \'keepdims\', \'name\'], varargs=None, keywords=None, … 333 …argspec: "args=[\'input_tensor\', \'axis\', \'keepdims\', \'name\'], varargs=None, keywords=None, … 337 …argspec: "args=[\'input_tensor\', \'axis\', \'keepdims\', \'name\'], varargs=None, keywords=None, … [all …]
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/external/tensorflow/tensorflow/tools/api/golden/v1/ |
D | tensorflow.math.pbtxt | 105 …argspec: "args=[\'input_tensor\', \'axis\', \'keepdims\', \'dtype\', \'name\', \'reduction_indices… 305 …argspec: "args=[\'input_tensor\', \'axis\', \'keepdims\', \'name\', \'reduction_indices\', \'keep_… 309 …argspec: "args=[\'input_tensor\', \'axis\', \'keepdims\', \'name\', \'reduction_indices\', \'keep_… 313 …argspec: "args=[\'input_tensor\', \'axis\', \'keepdims\', \'name\'], varargs=None, keywords=None, … 317 …argspec: "args=[\'input_tensor\', \'axis\', \'keepdims\', \'name\', \'reduction_indices\', \'keep_… 321 …argspec: "args=[\'input_tensor\', \'axis\', \'keepdims\', \'name\', \'reduction_indices\', \'keep_… 325 …argspec: "args=[\'input_tensor\', \'axis\', \'keepdims\', \'name\', \'reduction_indices\', \'keep_… 329 …argspec: "args=[\'input_tensor\', \'axis\', \'keepdims\', \'name\', \'reduction_indices\', \'keep_… 333 …argspec: "args=[\'input_tensor\', \'axis\', \'keepdims\', \'name\', \'reduction_indices\', \'keep_… 337 …argspec: "args=[\'input_tensor\', \'axis\', \'keepdims\', \'name\'], varargs=None, keywords=None, … [all …]
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D | tensorflow.sparse.pbtxt | 65 …argspec: "args=[\'sp_input\', \'axis\', \'keepdims\', \'reduction_axes\', \'keep_dims\'], varargs=… 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=…
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/external/tensorflow/tensorflow/python/keras/ |
D | constraints.py | 70 math_ops.reduce_sum(math_ops.square(w), axis=self.axis, keepdims=True)) 112 math_ops.square(w), axis=self.axis, keepdims=True))) 156 math_ops.reduce_sum(math_ops.square(w), axis=self.axis, keepdims=True))
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D | activations.py | 61 e = math_ops.exp(x - math_ops.reduce_max(x, axis=axis, keepdims=True)) 62 s = math_ops.reduce_sum(e, axis=axis, keepdims=True)
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/external/tensorflow/tensorflow/contrib/learn/python/learn/estimators/ |
D | kmeans_test.py | 49 return x / np.sqrt(np.sum(x * x, axis=-1, keepdims=True)) 221 keepdims=True) - 2 * np.dot(points, np.transpose(clusters)) + 222 np.transpose(np.sum(np.square(clusters), axis=1, keepdims=True))) 326 np.mean(normalize(self.points)[0:4, :], axis=0, keepdims=True))[ 329 np.mean(normalize(self.points)[4:, :], axis=0, keepdims=True))[ 393 np.mean(normalize(points)[0:2, :], axis=0, keepdims=True))[0], 395 np.mean(normalize(points)[2:4, :], axis=0, keepdims=True))[0], 397 np.mean(normalize(points)[4:, :], axis=0, keepdims=True))[0]
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/external/tensorflow/tensorflow/contrib/factorization/python/ops/ |
D | gmm_ops.py | 57 x -= math_ops.reduce_mean(x, 0, keepdims=True) 60 math_ops.square(x), 0, keepdims=True) / (num_points - 1) 317 math_ops.log(self._covs + 1e-3), 1, keepdims=True) 355 self._probs[shard_id], axis=1, keepdims=True) 379 self._w[shard_id], 0, keepdims=True) 459 math_ops.reduce_logsumexp(op, axis=2, keepdims=True), axis=0)
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D | kmeans_test.py | 49 return x / np.sqrt(np.sum(x * x, axis=-1, keepdims=True)) 214 np.sum(np.square(points), axis=1, keepdims=True) - 216 np.sum(np.square(clusters), axis=1, keepdims=True))) 359 keepdims=True))[0], 362 keepdims=True))[0] 426 np.mean(normalize(points)[0:2, :], axis=0, keepdims=True))[0], 428 np.mean(normalize(points)[2:4, :], axis=0, keepdims=True))[0], 430 keepdims=True))[0]
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/external/tensorflow/tensorflow/contrib/image/python/kernel_tests/ |
D | interpolate_spline_test.py | 112 keepdims=True) 119 keepdims=True) 145 keepdims=True) 152 keepdims=True)
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/external/tensorflow/tensorflow/python/layers/ |
D | normalization_test.py | 1114 means = np.mean(sub_batched, axis=0, keepdims=True) 1115 variances = np.var(sub_batched, axis=0, keepdims=True) 1117 avg_means = np.mean(means, axis=1, keepdims=True) 1118 avg_variances = np.mean(variances, axis=1, keepdims=True) 1167 means = np.mean(sub_batched, axis=(0, 2, 3), keepdims=True) 1168 variances = np.var(sub_batched, axis=(0, 2, 3), keepdims=True) 1170 avg_means = np.mean(means, axis=1, keepdims=True) 1171 avg_variances = np.mean(variances, axis=1, keepdims=True) 1221 means = np.mean(sub_batched, axis=(0, 3, 4), keepdims=True) 1222 variances = np.var(sub_batched, axis=(0, 3, 4), keepdims=True) [all …]
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