- Sort Score
- Result 10 results
- Languages All
Results 1 - 10 of 28 for tanh (0.12 sec)
-
src/math/tanh.go
} return z
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Mon Apr 11 16:34:30 UTC 2022 - 2.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/layout_optimization_move_transposes_begin.mlir
// CHECK: %[[ARG_TRANSPOSE:[0-9]*]] = "tf.Transpose"(%arg0, %[[ARG_PERM]]) // CHECK: %[[TANH:[0-9]*]] = "tf.Tanh"(%[[ARG_TRANSPOSE]]) {{.*}} tensor<1x8x4x4xf32> // CHECK: %[[ADD:[0-9]*]] = "tf.AddV2"(%[[TANH]], %[[TANH]]) {{.*}} tensor<1x8x4x4xf32> // CHECK: return %[[ADD]] %0 = "tf.Tanh"(%arg0) : (tensor<1x4x4x8xf32>) -> tensor<1x4x4x8xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 6.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfr/examples/mnist/ops_defs.py
elif act == 'TANH': return tf.raw_ops.Tanh(x=res) else: return res @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)
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/compiler/jit/tests/opens2s_gnmt_mixed_precision.golden_summary
Const 7 GreaterEqual 2 MatMul 1 Mul 5 Select 2 Sigmoid 3 Snapshot 1 Split 1 Tanh 2 cluster 22 size 28 Add 3 BiasAdd 1 Cast 1 ConcatV2 1 Const 5 GreaterEqual 1 MatMul 1 Mul 5 Select 3 Sigmoid 3 Snapshot 1 Split 1 Tanh 2 cluster 23 size 423 Add 12 AddN 28 BiasAddGrad 6 BroadcastGradientArgs 12 Cast 12
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Jan 06 10:38:14 UTC 2023 - 5K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/layout_optimization_move_transposes_end.mlir
// CHECK: %[[RES_PERM:.*]] = "tf.Const"() <{value = dense<[0, 3, 1, 2]> : tensor<4xi32>}> // CHECK: %[[TANH:[0-9]*]] = "tf.Tanh"(%arg0) {{.*}} tensor<1x4x4x8xf32> // CHECK: %[[RES_TRANSPOSE:[0-9]*]] = "tf.Transpose"(%[[TANH]], %[[RES_PERM]]) {{.*}} tensor<1x8x4x4xf32> // CHECK: return %[[RES_TRANSPOSE]] %0 = "tf.Const"() {value = dense<[0, 3, 1, 2]> : tensor<4xi32>} : () -> tensor<4xi32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 9.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/mlir2flatbuffer/unidirectional_sequence_rnn.mlir
// CHECK-NEXT: builtin_options_type: SequenceRNNOptions, // CHECK-NEXT: builtin_options: { // CHECK-NEXT: time_major: true, // CHECK-NEXT: fused_activation_function: TANH // CHECK-NEXT: } // CHECK-NEXT: } ], // CHECK-NEXT: name: "main" // CHECK-NEXT: } ], // CHECK-NEXT: description: "MLIR Converted.", // CHECK-NEXT: buffers: [ { // CHECK-EMPTY:
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jul 14 16:41:28 UTC 2022 - 3.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfr/examples/mnist/mnist_ops_test.py
tf.function(gen_mnist_ops.new_conv2d), ops_defs._composite_conv_add_relu, kwargs) def test_new_conv2d_tanh(self): self.skipTest('Fix tanh gradients') input_ = tf.random.uniform([1, 4, 4, 1]) filter_ = tf.random.uniform([2, 2, 1, 8]) bias = tf.zeros([8]) kwargs = { 'input_': input_, 'filter_': filter_, 'bias': bias,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Sep 28 21:37:05 UTC 2021 - 4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/quantize-dynamic-range-float16.mlir
%5, %6, %7, %8, %9, %9, %9, %10, %11, %10, %10, %9, %9, %recurrent_input, %cell_input, %9, %9, %9, %9) { cell_clip = 1.000000e+01 : f32, fused_activation_function = "TANH", proj_clip = 0.000000e+00 : f32, time_major = false} : ( tensor<1x2x3xf32>, tensor<1x1xf32>, tensor<1x1xf32>, tensor<1x1xf32>, tensor<1x1xf32>,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 4.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/tests/tf_to_corert/basic.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 08 00:18:59 UTC 2024 - 3.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfr/README.md
res = tf.raw_ops.Add(x=res, y=bias) if act == 'RELU': return tf.raw_ops.Relu(features=res) elif act == 'RELU6': return tf.raw_ops.Relu6(features=res) elif act == 'TANH': return tf.raw_ops.Tanh(x=res) else: return res ``` Besides defining new ops, composition can be specified for an existing op for portability. The following code defines the semantics of `AddNOp`: ```python @Composite('AddNOp')
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Mar 29 18:32:13 UTC 2022 - 6.2K bytes - Viewed (0)