| /external/tensorflow/tensorflow/contrib/boosted_trees/python/kernel_tests/ |
| D | stats_accumulator_ops_test.py | 47 num_updates, partition, bucket_ids, grads, hessians = accumulator.flush(
49 num_updates, partition, bucket_ids, grads, hessians = sess.run(
50 [num_updates, partition, bucket_ids, grads, hessians])
52 result = _AccumulatorResultToDict(partition, bucket_ids, grads, hessians)
75 num_updates, partition, bucket_ids, grads, hessians = accumulator.flush(
77 num_updates, partition, bucket_ids, grads, hessians = sess.run(
78 [num_updates, partition, bucket_ids, grads, hessians])
80 result = _AccumulatorResultToDict(partition, bucket_ids, grads, hessians)
109 num_updates, partition, feature, grads, hessians = accumulator.flush(
111 num_updates, partition, feature, grads, hessians = sess.run(
[all …]
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| /external/tensorflow/tensorflow/python/ops/ |
| D | gradients_util.py | 301 def _VerifyGeneratedGradients(grads, op): argument
316 if len(grads) != len(op.inputs):
318 "inputs %d" % (len(grads), op.node_def, len(op.inputs)))
626 grads = {}
630 _SetGrad(grads, y, grad_y)
648 _SetGrad(grads, y, loop_state.ZerosLikeForExit(y))
658 out_grads = _AggregatedGrads(grads, op, gradient_uid, loop_state,
768 _SetGrad(grads, t_in, in_grad)
773 _UpdatePendingAndEnqueueReady(grads, op, queue, pending_count, loop_state,
778 return [_GetGrad(grads, x, unconnected_gradients) for x in xs]
[all …]
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| D | cudnn_rnn_grad.py | 25 def _cudnn_rnn_backward(op, *grads): argument
38 output_backprop=grads[0],
39 output_h_backprop=grads[1],
40 output_c_backprop=grads[2],
77 def _cudnn_rnn_backwardv3(op, *grads): argument
92 output_backprop=grads[0],
93 output_h_backprop=grads[1],
94 output_c_backprop=grads[2],
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| D | gradients_test.py | 159 grads = gradients.gradients(z, [x])
160 self.assertTrue(all(x is not None for x in grads))
170 grads = gradients.gradients(z, [x, y])
171 self.assertTrue(all(x is not None for x in grads))
172 self.assertEqual(6.0, grads[0].eval())
180 grads = gradients.gradients(
184 self.assertTrue(all(x is not None for x in grads))
185 self.assertEqual(20.0, grads[0].eval())
186 self.assertEqual(10.0, grads[1].eval())
194 grads = gradients.gradients(
[all …]
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| D | while_v2.py | 248 def _WhileGrad(op, *grads): # pylint: disable=invalid-name argument
262 grads = [_preprocess_grad(grad, body_out, while_out)
264 in zip(grads, body_graph.outputs, while_op.outputs)]
270 body_graph.outputs, body_graph.inputs, grads) if grad is not None])
303 grads, body_grad_graph, loop_vars, while_op.inputs)
331 return _get_structured_grad_output(outputs, grads, body_grad_graph)
423 def _create_grad_func(ys, xs, grads, cond_graph, body_graph, name, while_op, argument
443 assert len(ys) == len(grads)
449 args = [counter, maximum_iterations, total_iters] + list(grads)
555 def _get_structured_grad_output(outputs, grads, body_grad_graph): argument
[all …]
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| D | cond_v2.py | 90 def _IfGrad(op, *grads): # pylint: disable=invalid-name argument
104 true_graph, grads, util.unique_grad_fn_name(true_graph.name))
106 false_graph, grads, util.unique_grad_fn_name(false_graph.name))
260 def _grad_fn(func_graph, grads): argument
278 assert len(func_graph.outputs) == len(grads)
281 for y, grad_y in zip(func_graph.outputs, grads):
309 def _create_grad_func(func_graph, grads, name): argument
313 lambda: _grad_fn(func_graph, grads), [], {},
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| /external/tensorflow/tensorflow/java/src/test/java/org/tensorflow/op/core/ |
| D | GradientsTest.java | 47 Gradients grads = Gradients.create(scope, y1, Arrays.asList(x, y0)); in createGradients() local
49 assertNotNull(grads); in createGradients()
50 assertNotNull(grads.dy()); in createGradients()
51 assertEquals(2, grads.dy().size()); in createGradients()
56 sess.runner().feed(x, c).fetch(grads.dy(0)).fetch(grads.dy(1)).run())) { in createGradients()
74 Gradients grads = Gradients.create(scope, Arrays.asList(y0, y1), Arrays.asList(x)); in createGradientsWithSum() local
76 assertNotNull(grads); in createGradientsWithSum()
77 assertNotNull(grads.dy()); in createGradientsWithSum()
78 assertEquals(1, grads.dy().size()); in createGradientsWithSum()
82 new TestUtil.AutoCloseableList<>(sess.runner().feed(x, c).fetch(grads.dy(0)).run())) { in createGradientsWithSum()
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| /external/tensorflow/tensorflow/core/kernels/ |
| D | crop_and_resize_op.cc | 346 const Tensor& grads = context->input(0); in ComputeAsync() local
355 OP_REQUIRES_ASYNC(context, grads.dims() == 4, in ComputeAsync()
357 grads.shape().DebugString()), in ComputeAsync()
359 const int crop_height = grads.dim_size(1); in ComputeAsync()
360 const int crop_width = grads.dim_size(2); in ComputeAsync()
368 context, grads.dim_size(0) == num_boxes, in ComputeAsync()
389 context, grads.dim_size(3) == depth, in ComputeAsync()
402 const Tensor& grads = context->input(0); in ComputeAsync() local
406 context->eigen_device<Device>(), grads.tensor<float, 4>(), in ComputeAsync()
429 typename TTypes<float, 4>::ConstTensor grads, in operator ()()
[all …]
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| D | crop_and_resize_op_gpu.cu.cc | 388 typename TTypes<float, 4>::ConstTensor grads, in operator ()()
397 const int num_boxes = grads.dimension(0); in operator ()()
398 const int crop_height = grads.dimension(1); in operator ()()
399 const int crop_width = grads.dimension(2); in operator ()()
400 const int depth = grads.dimension(3); in operator ()()
427 grads.data(), boxes.data(), box_ind.data(), num_boxes, batch, in operator ()()
438 typename TTypes<float, 4>::ConstTensor grads, in operator ()()
447 const int num_boxes = grads.dimension(0); in operator ()()
448 const int crop_height = grads.dimension(1); in operator ()()
449 const int crop_width = grads.dimension(2); in operator ()()
[all …]
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| /external/tensorflow/tensorflow/python/debug/lib/ |
| D | debug_gradients_test.py | 63 grads = gradients_impl.gradients(y, [self.u, self.v])
64 self.assertEqual(2, len(grads))
65 u_grad = grads[0]
66 v_grad = grads[1]
94 grads = gradients_impl.gradients(y, [self.u, self.v])
95 self.assertEqual(2, len(grads))
96 u_grad = grads[0]
97 v_grad = grads[1]
205 grads = gradients_impl.gradients(y, [self.u, self.v])
206 self.assertEqual(2, len(grads))
[all …]
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| /external/tensorflow/tensorflow/contrib/eager/python/examples/revnet/ |
| D | revnet_test.py | 35 grads, loss = model.compute_gradients(
38 zip(grads, model.trainable_variables), global_step=global_step)
79 def _check_grad_angle_combined(self, grads, grads_true): argument
93 g1_all = tf.concat(_combine(grads), axis=0)
105 grads, loss = self.model.compute_gradients(
108 self.assertTrue(isinstance(grads, list))
110 self.assertEqual(len(grads), len(vars_))
111 for grad, var in zip(grads, vars_):
120 self.assertAllClose(grads, grads_true, rtol=1e-4, atol=1e-4)
121 self._check_grad_angle_combined(grads, grads_true)
[all …]
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| D | blocks_test.py | 119 def _check_grad_angle(self, grads, grads_true, atol=1e0): argument
121 for g1, g2 in zip(grads, grads_true):
155 grads = tape.gradient(y, [x] + vars_, output_gradients=dy)
156 dx_true, dw_true = grads[0], grads[1:]
184 grads = tape.gradient(y, [x] + vars_, output_gradients=dy)
185 dx_true, dw_true = grads[0], grads[1:]
259 grads = tape.gradient(
261 dx_true, dw_true = grads[0], grads[1:]
|
| /external/tensorflow/tensorflow/python/keras/mixed_precision/experimental/ |
| D | loss_scale_optimizer.py | 76 grads = [g for g, _ in grads_and_vars]
78 scaled_grads = self._scale_grads(grads)
83 grads = self._optimizer.get_gradients(loss, params)
84 return self._scale_grads(grads)
93 def _scale_grads(self, grads): argument
95 return [None if g is None else g * loss_scale_reciprocal for g in grads]
|
| /external/tensorflow/tensorflow/python/keras/ |
| D | optimizers.py | 92 grads = K.gradients(loss, params)
93 if None in grads:
100 grads = [clip_ops.clip_by_norm(g, self.clipnorm) for g in grads]
102 grads = [
104 for g in grads
106 return grads
186 grads = self.get_gradients(loss, params)
198 for p, g, m in zip(params, grads, moments):
256 grads = self.get_gradients(loss, params)
267 for p, g, a in zip(params, grads, accumulators):
[all …]
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| /external/tensorflow/tensorflow/core/graph/ |
| D | gradients.cc | 101 static Node* AddSymGrad(Graph* g, Node* n, gtl::ArraySlice<NodeOut> grads) { in AddSymGrad() argument
104 CHECK_EQ(num_y, grads.size()); in AddSymGrad()
121 for (const NodeOut& nout : grads) { in AddSymGrad()
230 auto* grads = &iter->second; in BackpropAlongEdge() local
231 grads->push_back(dst_grad); in BackpropAlongEdge()
298 const auto& grads = iter->second; in SumGradients() local
299 if (grads.empty()) { in SumGradients()
304 if (grads.size() == 1) { in SumGradients()
306 return grads[0]; in SumGradients()
312 for (const NodeOut& nout : grads) { in SumGradients()
[all …]
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| /external/tensorflow/tensorflow/python/kernel_tests/ |
| D | gather_nd_op_test.py | 258 grads = gradients_impl.gradients([outputs], [inputs], [grad_vals])[0]
261 assert np.array_equal(expected_grads, self.evaluate(grads))
270 grads = gradients_impl.gradients([outputs], [inputs], [grad_vals])[0]
273 self.assertIndexedSlices(grads)
274 self.assertAllEqual(expected_grads, ops.convert_to_tensor(grads).eval())
286 grads = gradients_impl.gradients([outputs], [inputs], [grad_vals])[0]
290 self.assertAllEqual(expected_grads, self.evaluate(grads))
313 grads = gradients_impl.gradients([outputs], [inputs], [grad_vals])[0]
320 self.assertAllEqual(expected_grads, self.evaluate(grads))
332 grads = gradients_impl.gradients([outputs], [inputs], [grad_vals])[0]
[all …]
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| D | dynamic_stitch_op_test.py | 154 grads = gradients_impl.gradients(stitched_t, indices + data,
156 self.assertEqual(grads[:3], [None] * 3) # Indices have no gradients
157 for datum, grad in zip(data, self.evaluate(grads[3:])):
257 grads = gradients_impl.gradients(stitched_t, indices + data,
259 self.assertEqual(grads[:3], [None] * 3) # Indices have no gradients
260 for datum, grad in zip(data, self.evaluate(grads[3:])):
294 grads = gradients_impl.gradients(stitched_t, indices + data,
296 self.assertEqual(grads[:3], [None] * 3) # Indices have no gradients
297 for datum, grad in zip(data, self.evaluate(grads[3:])):
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| D | cond_v2_test.py | 429 grads = nesting_fn()
431 return grads, pred_outer, pred_inner
434 grads, pred_outer, pred_inner = build_graph()
437 sess.run(grads, {
442 sess.run(grads, {
447 sess.run(grads, {
452 sess.run(grads, {
492 grads = nesting_fn()
494 return grads, pred_outer, pred_inner
497 grads, pred_outer, pred_inner = build_graph()
[all …]
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| /external/tensorflow/tensorflow/contrib/layers/python/layers/ |
| D | rev_block_lib.py | 69 for grads in zip(*lists_of_grads):
70 grads = [g for g in grads if g is not None]
71 if grads:
72 acc_grads.append(math_ops.add_n(grads))
321 for idxs, grads in list(zip(f_vars_idxs, f_var_grads)) + list(
323 for i, grad in zip(idxs, grads):
563 grads = gradients_impl.gradients(outputs, inputs + variables,
568 grads = _tuple_with_data_dep(grads)
570 grads = control_flow_ops.tuple(grads)
572 grad_inputs = grads[:len(inputs)]
[all …]
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| D | rev_block_lib_test.py | 152 grads = gradients_impl.gradients(loss, wrt)
156 y_val, yd_val, gd_val, g_val = sess.run([y, y_rev, grads_rev, grads])
301 for grads in zip(all_grads_val):
302 current = grads[0]
303 for g in grads[1:]:
343 grads = gradients_impl.gradients(out, [inputs] + tvars)
344 for grad in grads:
391 grads = gradients_impl.gradients(layer_list[-1], layer_list[0])
393 sess.run(grads)
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| /external/tensorflow/tensorflow/python/keras/optimizer_v2/ |
| D | optimizer_v2.py | 331 grads = tape.gradient(loss_value, var_list, grad_loss)
334 grads = [clip_ops.clip_by_norm(g, self.clipnorm) for g in grads]
336 grads = [
338 for g in grads
341 grads_and_vars = list(zip(grads, var_list))
364 grads = gradients.gradients(loss, params)
365 if None in grads:
372 grads = [clip_ops.clip_by_norm(g, self.clipnorm) for g in grads]
374 grads = [
376 for g in grads
[all …]
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| D | adadelta_test.py | 53 grads = constant_op.constant([grad, grad], dtype=dtype)
71 zip([grads, grads], [var0, var1]))
100 adadelta_opt.apply_gradients(zip([grads, grads], [var0, var1]))
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| /external/tensorflow/tensorflow/contrib/training/python/training/ |
| D | training.py | 441 grads = optimizer.compute_gradients(
449 grads = transform_grads_fn(grads)
454 add_gradients_summaries(grads)
457 grad_updates = optimizer.apply_gradients(grads, global_step=global_step)
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| /external/tensorflow/tensorflow/python/training/ |
| D | adadelta_test.py | 53 grads = constant_op.constant([grad, grad], dtype=dtype)
71 zip([grads, grads], [var0, var1]))
115 adadelta_opt.apply_gradients(zip([grads, grads], [var0, var1]))
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| /external/tensorflow/tensorflow/contrib/slim/python/slim/ |
| D | learning.py | 417 def transform_grads_fn(grads): argument
420 grads = multiply_gradients(grads, gradient_multipliers)
425 grads = clip_gradient_norms(grads, clip_gradient_norm)
426 return grads
|