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Results 1 - 10 of 79 for Brad (0.66 sec)
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src/strings/replace_test.go
testCases = append(testCases, testCase{capitalLetters, "brad", "BrAd"}, testCase{capitalLetters, Repeat("a", (32<<10)+123), Repeat("A", (32<<10)+123)}, testCase{capitalLetters, "", ""}, testCase{inc, "brad", "csbe"}, testCase{inc, "\x00\xff", "\x01\x00"}, testCase{inc, "", ""}, testCase{NewReplacer("a", "1", "a", "2"), "brad", "br1d"}, ) // repeat maps "a"->"a", "b"->"bb", "c"->"ccc", ...
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Fri Feb 24 22:53:05 UTC 2017 - 14.1K bytes - Viewed (0) -
api/go1.4.txt
# CL 134210043 archive/zip: add Writer.Flush, Brad Fitzpatrick <******@****.***> pkg archive/zip, method (*Writer) Flush() error # CL 97140043 compress/flate: add Reset() to allow reusing large buffers to compress multiple buffers, James Robinson <******@****.***> pkg compress/flate, type Resetter interface { Reset } pkg compress/flate, type Resetter interface, Reset(io.Reader, []uint8) error pkg compress/zlib, type Resetter interface { Reset }
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Fri Dec 12 03:01:01 UTC 2014 - 34K bytes - Viewed (0) -
src/database/sql/sql_test.go
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Thu May 23 18:42:28 UTC 2024 - 111.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfr/examples/mnist/ops_defs.py
@tf.RegisterGradient('NewConv2D') def _conv_add_relu_grad(op: ops.Operation, grad): act = op.get_attr('act') y = op.outputs[0] if act == 'RELU': grad = gen_nn_ops.relu_grad(grad, y) elif act == 'RELU6': grad = gen_nn_ops.relu6_grad(grad, y) elif act == 'TANH': y = math_ops.conj(y) grad = gen_math_ops.tanh_grad(y, grad) broadcast_shape = tf.shape(y) input_value_shape = tf.shape(op.inputs[2])
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Aug 31 20:23:51 UTC 2023 - 6.8K bytes - Viewed (0) -
tensorflow/cc/gradients/math_grad.cc
std::vector<Output>* grad_outputs) { auto grad = grad_inputs[0]; auto two_over_root_pi = Cast(scope, Const(scope, 2 / std::sqrt(M_PI)), grad.type()); Scope grad_scope = scope.WithControlDependencies(grad); auto x = ConjugateHelper(grad_scope, op.input(0)); // grad * 2/sqrt(pi) * exp(-x**2) auto dx = Mul(grad_scope, Mul(grad_scope, grad, two_over_root_pi),
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Aug 25 18:20:20 UTC 2023 - 50.7K bytes - Viewed (0) -
tensorflow/cc/gradients/nn_grad.cc
auto multiply_result = Multiply(scope, subtraction_result, logits_softmax); grad = Add(scope, grad, multiply_result); } auto minus_log_softmax = Multiply(scope, LogSoftmax(scope, logits), -1.0f); grad_outputs->push_back(grad); grad_outputs->push_back(BroadcastMul(scope, grad_loss, minus_log_softmax)); return scope.status(); }
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/compiler/mlir/tensorflow/tests/decompose_resource_ops.mlir
// CHECK: [[GRAD_SQUARE:%.*]] = "tf.Mul"([[GRAD]], [[GRAD]]) : (tensor<f32>, tensor<f32>) -> tensor<f32> // CHECK: [[NEW_ACC:%.*]] = "tf.AddV2"([[OLD_ACC]], [[GRAD_SQUARE]]) : (tensor<*xf32>, tensor<f32>) -> tensor<*xf32> // CHECK: [[LR_MULTIPLY:%.*]] = "tf.Mul"([[LR]], [[GRAD]]) : (tensor<f32>, tensor<f32>) -> tensor<f32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 22 19:47:48 UTC 2024 - 51.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/decompose_resource_ops.td
(CreateTFReadVariableOp $src_op, $grad, $ms_resource), (TF_AddV2Op:$ms_new (TF_MulOp (TF_MulOp $grad, $grad), (TF_SubOp $one, $rho) ), (TF_MulOp (CreateTFReadVariableOp $src_op, $grad, $ms_resource), $rho ) ), (TF_AssignVariableOp $ms_resource, $ms_new, (CreateConstBoolAttrFalse)), // mg = grad * (one - rho) + mg * rho;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 22 19:47:48 UTC 2024 - 20.7K bytes - Viewed (0) -
tensorflow/c/experimental/gradients/math_grad.cc
/* Given upstream grad U and a Sub op A-B, the gradients are: * * dA = U * dB = -U * */ // Grad for A DCHECK(grad_outputs[0]); grad_inputs[0] = grad_outputs[0]; grad_inputs[0]->Ref(); // Grad for B // negate the upstream grad std::string name = "Neg_Sub_Grad_B"; TF_RETURN_IF_ERROR(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Feb 28 13:53:47 UTC 2024 - 15.2K bytes - Viewed (0) -
tensorflow/c/experimental/gradients/nn_grad.cc
absl::Span<AbstractTensorHandle*> grad_inputs) override { // Grad for Softmax Input TF_RETURN_IF_ERROR(BroadcastMul( ctx, grad_outputs[0], forward_outputs_[1], grad_inputs.subspan(0, 1))); // upstream_grad * local softmax grad // Grad for labels is null grad_inputs[1] = nullptr; return absl::OkStatus(); }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 09 06:38:45 UTC 2024 - 5.7K bytes - Viewed (0)