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Results 1 - 10 of 22 for backprop (0.25 sec)
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tensorflow/cc/framework/gradients.cc
DCHECK(while_ctx != nullptr); // Record 'summed_grads' as the backprop input associated with 'exit_node' std::map<Node*, Output>& backprops = while_backprops_[while_ctx]; DCHECK(backprops.find(exit_node) == backprops.end()); backprops[exit_node] = summed_grads; // Wait until we have all exit nodes' backprops collected before processing // the while loop.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Apr 13 05:57:22 UTC 2024 - 22K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/tpu_space_to_depth_pass.cc
// Build new BackPropFilterOp. auto loc = backprop.getLoc(); auto new_backprop = builder.create<TF::Conv2DBackpropFilterOp>( loc, new_result_type, input, new_filter_sizes, backprop.getOutBackprop(), strides, backprop.getUseCudnnOnGpu(), backprop.getPadding(), backprop.getExplicitPaddings(), backprop.getDataFormat(), backprop.getDilations());
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 29.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/lower_tf.td
// computes loss and backprop of the loss with respect to 'features'. // // Softmax cross entropy loss is defined as follows: // // loss = Sum(-labels * Log(Exp(features) / Sum(Exp(features))) // loss = Sum(-labels * LogSoftmax(features)) // // Computing gradient of the loss with respect to features gives us, // // backprop = (Exp(features) / Sum(Exp(features))) - labels
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 04 13:30:42 UTC 2024 - 24.7K bytes - Viewed (0) -
tensorflow/c/eager/tape.h
// any gradients to be computed). // // Finally, we start a backprop stack with a set of tape entries for which we // have all gradients available. This set usually is a subset of the set of // targets (not all since targets which have outputs in the tape will not have // gradients available initially). // // Then we repeatedly pop an entry from the stack, run its backprop, and update
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 02 12:40:29 UTC 2024 - 47.2K bytes - Viewed (0) -
tensorflow/cc/gradients/nn_grad.cc
// We multiply the backprop for cost with the gradients - op.output[1]. // There is no gradient for labels. // The outputs of the network are at input index 0. auto logits = op.input(0); // The "truth" labels are at index 1. auto softmax_grad = op.output(1); // The loss is the output at index 0, and backprop is the output at index 1. auto grad_loss = grad_inputs[0];
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 27 23:34:33 UTC 2022 - 24.5K bytes - Viewed (0) -
tensorflow/cc/gradients/nn_grad_test.cc
auto y = tensorflow::ops::SoftmaxCrossEntropyWithLogits(scope_, logits, labels); // Note the reversal of the backprop and loss orders. Issue #18734 has been // opened for this. RunTest({logits, labels}, {logits_shape, logits_shape}, {y.backprop, y.loss}, {logits_shape, loss_shape}); } TEST_F(NNGradTest, LogSoftmaxGrad) { TensorShape shape({5, 3});
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Mar 22 20:45:22 UTC 2022 - 15K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tpu_space_to_depth_pass.mlir
// CHECK: %[[BACKPROP:.*]] = "tf.Conv2DBackpropFilter" // CHECK-SAME: strides = [1, 1, 1, 1] // CHECK-SAME: (tensor<2x115x115x12xf32>, tensor<4xi32>, tensor<2x112x112x64xf32>) -> tensor<4x4x12x64xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 37.4K bytes - Viewed (0) -
tensorflow/cc/framework/gradients_test.cc
{dx, dy, dz}, &grad_outputs)); } } CompareTestAndExpectedGraphs(); } TEST_F(GradientsTest, StackUnstack_StopBackprop) { // Tests that backprop stops before calculating gradients for Stack (because // only gradients w.r.t the output of Stack are requested). for (const bool expected : {false, true}) { const Scope& scope = expected ? scope_expected_ : scope_test_;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Apr 15 15:13:38 UTC 2023 - 25K bytes - Viewed (0) -
tensorflow/c/while_loop_test.cc
Add(params_->body_inputs[0], {one, 0}, params_->body_graph, s_); ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_); params_->body_outputs[0] = {add, 0}; ExpectOK(); // Create backprop graph TF_Output grad_output; TF_AddGradients(graph_, outputs_.data(), outputs_.size(), inputs_.data(), 1, nullptr, s_, &grad_output); ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 11 06:05:56 UTC 2024 - 15.3K bytes - Viewed (0) -
pkg/ctrlz/assets/static/js/bootstrap-4.0.0.min.js
tScrollbar(),t(e._element).trigger(h.HIDDEN)})},p._removeBackdrop=function(){this._backdrop&&(t(this._backdrop).remove(),this._backdrop=null)},p._showBackdrop=function(e){var n=this,i=t(this._element).hasClass(d)?d:"";if(this._isShown&&this._config.backdrop){var s=P.supportsTransitionEnd()&&i;if(this._backdrop=document.createElement("div"),this._backdrop.className=u,i&&t(this._backdrop).addClass(i),t(this._backdrop).appendTo(document.body),t(this._element).on(h.CLICK_DISMISS,function(t){n._ignor...
Registered: Fri Jun 14 15:00:06 UTC 2024 - Last Modified: Tue May 23 17:08:31 UTC 2023 - 47.8K bytes - Viewed (0)