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Results 1 - 10 of 15 for ctanh (0.04 sec)
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tensorflow/compiler/mlir/lite/tests/prepare-quantize-post-training-16bits.mlir
%9, %9, %9, %9) { asymmetric_quantize_inputs = false, cell_clip = 1.000000e+01 : f32, effective_hidden_scale_intermediate = tensor<0x!quant.calibrated<f32<0.0:1.0>>>, fused_activation_function = "TANH", input_to_cell_intermediate = tensor<0xf32>, input_to_forget_intermediate = tensor<0xf32>, input_to_input_intermediate = tensor<0xf32>, input_to_output_intermediate = tensor<0xf32>,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 26.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/flatbuffer2mlir/lstm.mlir
"tfl.lstm"(%arg0, %arg1, %arg2, %arg3, %arg4, %arg5, %arg6, %arg7, %arg8, %cst, %cst, %cst, %arg9, %arg10, %arg11, %arg12, %arg13, %arg14, %arg19, %arg20, %arg15, %arg16, %arg17, %arg18) ({}) {cell_clip = 1.000000e+01 : f32, fused_activation_function = "TANH", input_to_input_intermediate = tensor<0x!quant.uniform<i16:f32, 0.0049890000373125076>>, input_to_forget_intermediate = tensor<0x!quant.uniform<i16:f32, 0.0078849997371435165>>, input_to_cell_intermediate = tensor<0x!quant.uniform<i16:f32, 0.0087630003690719604>>,...
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 20.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/legalize_tf.cc
// Populate attributes. SmallVector<NamedAttribute, 4> attributes; // Activation will always be tanh. attributes.push_back(rewriter.getNamedAttr("fused_activation_function", rewriter.getStringAttr("TANH"))); // cell_clip. attributes.push_back( rewriter.getNamedAttr("cell_clip", rewriter.getF32FloatAttr(0.0))); // proj_clip.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon May 20 20:06:54 UTC 2024 - 45.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/optimize.mlir
%4 = mhlo.exponential %3 : tensor<13x13x13xf32> %5 = mhlo.tanh %3 : tensor<13x13x13xf32> return %4, %5 : tensor<13x13x13xf32>, tensor<13x13x13xf32> // CHECK: "mhlo.pad"(%arg0, %0) <{ // CHECK-SAME: edge_padding_high = dense<2> : tensor<3xi64>,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Apr 06 15:32:52 UTC 2024 - 22.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/quantization_lib/quantization_config.h
// inconsistent with Conv 1x1 which always performs per channel quantization. bool disable_per_channel_for_dense_layers = false; // Whether to use fixed output ranges of the activation ops (tanh, sigmoid, // etc.) and not infer weight constants. // If this option is set, quantization emulation ops should be placed after // the ops in the input graph. This flag should be set to false for
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Mar 13 10:16:19 UTC 2024 - 10.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/utils/lstm_utils.cc
input_cell_state_, input_layer_norm_coefficients_, forget_layer_norm_coefficients_, cell_layer_norm_coefficients_, output_layer_norm_coefficients_, builder_.getStringAttr("TANH"), builder_.getF32FloatAttr(10.0), builder_.getF32FloatAttr(0.0), mlir::TFL::LSTMKernelTypeAttr::get(builder_.getContext(), mlir::TFL::LSTMKernelType::FULL),
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 36.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/flatbuffer2mlir/vhlo.mlir
//CHECK-NEXT: return %0 : tensor<1x30x1xi32> //CHECK-NEXT:} func.func @tanh(%arg0: tensor<1x1x1x96xf32>) -> tensor<1x1x1x96xf32> { %0 = "vhlo.tanh_v1" (%arg0) : (tensor<1x1x1x96xf32>) -> tensor<1x1x1x96xf32> func.return %0 : tensor<1x1x1x96xf32> } //CHECK:func.func private @tanh(%arg0: tensor<1x1x1x96xf32>) -> tensor<1x1x1x96xf32> {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Mar 14 19:15:40 UTC 2024 - 31.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/schema/schema_v3b.fbs
// create another op called RELU1. RELU_N1_TO_1 = 20, RELU6 = 21, RESHAPE = 22, RESIZE_BILINEAR = 23, RNN = 24, SOFTMAX = 25, SPACE_TO_DEPTH = 26, SVDF = 27, TANH = 28, CONCAT_EMBEDDINGS = 29, SKIP_GRAM = 30, CALL = 31, CUSTOM = 32, EMBEDDING_LOOKUP_SPARSE = 33, PAD = 34, UNIDIRECTIONAL_SEQUENCE_RNN = 35, GATHER = 36, BATCH_TO_SPACE_ND = 37,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 28 14:28:27 UTC 2024 - 30K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/post-quantize.mlir
%cst_2, %cst_2, %cst_2, %cst_7, %cst_7, %cst_7, %cst_7, %cst_2, %cst_2, %cst_1, %cell_input, %cst_2, %cst_2, %cst_2, %cst_2) {cell_clip = 1.000000e+01 : f32, fused_activation_function = "TANH", proj_clip = 0.000000e+00 : f32, time_major = false} : ( tensor<1x28x28x!quant.uniform<i8:f32, 0.003:-128>>,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 19.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/schema/schema.fbs
// create another op called RELU1. RELU_N1_TO_1 = 20, RELU6 = 21, RESHAPE = 22, RESIZE_BILINEAR = 23, RNN = 24, SOFTMAX = 25, SPACE_TO_DEPTH = 26, SVDF = 27, TANH = 28, CONCAT_EMBEDDINGS = 29, SKIP_GRAM = 30, CALL = 31, CUSTOM = 32, EMBEDDING_LOOKUP_SPARSE = 33, PAD = 34, UNIDIRECTIONAL_SEQUENCE_RNN = 35, GATHER = 36, BATCH_TO_SPACE_ND = 37,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 03 18:01:23 UTC 2024 - 41.7K bytes - Viewed (0)