- Sort Score
- Result 10 results
- Languages All
Results 101 - 110 of 196 for conv2 (0.04 sec)
-
tensorflow/compiler/mlir/quantization/tensorflow/passes/quantized_function_library_xla_weight_only.mlir
// Use identity op to avoid the filter being constant-folded. %identity = "tf.Identity"(%filter) : (tensor<*xi8>) -> tensor<*xi8> %2 = "tf.Cast"(%identity) {Truncate = false} : (tensor<*xi8>) -> tensor<*xf32> %3 = "tf.Conv2D"(%input, %2) { padding = "VALID", strides = [1, 1, 1, 1], attr_map = "strides:0,use_cudnn_on_gpu:1,padding:2,explicit_paddings:3,dilations:4" } : (tensor<*xf32>, tensor<*xf32>) -> tensor<*xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Mar 03 15:43:38 UTC 2023 - 7K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/lift_quantizable_spots_as_functions_drq_min_elements.mlir
func.func @not_lift_float_conv(%arg0: tensor<1x3x4x512xf32>) -> (tensor<*xf32>) { %cst = "tf.Const"() {value = dense<3.000000e+00> : tensor<2x3x512x512xf32>} : () -> tensor<2x3x512x512xf32> %0 = "tf.Conv2D"(%arg0, %cst) { data_format = "NHWC", device = "", dilations = [1, 1, 1, 1], explicit_paddings = [], padding = "SAME", strides = [1, 1, 2, 1], use_cudnn_on_gpu = true
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 2.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/quantize/quantize_weight_only.mlir
// CHECK: %[[CONV:.+]] = stablehlo.convolution(%[[ARG1]], %[[ARG2]]) // CHECK-SAME: (tensor<1x3x4x3xf32>, tensor<2x3x3x2x!quant.uniform<i8:f32, 6.000000e-03:-128>>) -> tensor<1x3x4x2xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 14 17:10:32 UTC 2024 - 4.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/prepare_tf.cc
// Only rank size four input will be only available by the tf.Conv2D // operator verification. if (!input_type || input_type.isDynamicDim(3)) { return failure(); } // Check if the given op is based on grouped convolution. // Dim size zero will be verified by the tf.Conv2D operator verification. if (input_type.getDimSize(3) % filter_type.getDimSize(2) != 0) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 28 21:49:50 UTC 2024 - 64.6K bytes - Viewed (0) -
src/cmd/compile/internal/typecheck/_builtin/runtime.go
func countrunes(string) int // Convert non-interface type to the data word of a (empty or nonempty) interface. func convT(typ *byte, elem *any) unsafe.Pointer // Same as convT, for types with no pointers in them. func convTnoptr(typ *byte, elem *any) unsafe.Pointer // Specialized versions of convT for specific types. // These functions take concrete types in the runtime. But they may
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Tue May 21 21:08:03 UTC 2024 - 10.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/end2end/conv_2d_nchw.pbtxt
} } attr { key: "_class" value { list { s: "loc:@conv_net_2d/conv_2d_0/w" } } } } node { name: "conv_net_2d_1/conv_2d_0/convolution" op: "Conv2D" input: "input" input: "conv_net_2d/conv_2d_0/w/read" attr { key: "T" value { type: DT_FLOAT } } attr { key: "data_format" value { s: "NCHW" }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Dec 03 03:26:13 UTC 2021 - 3.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/quantized_function_library_tf_drq.mlir
%5 = "tf.MatMul"(%1, %3) { attr_map = "transpose_a:0,transpose_b:1" } : (tensor<*xi32>, tensor<*xi32>) -> tensor<*xi32> func.return %5 : tensor<*xi32> } // Conv2D with int32 accumulation func.func private @internal_conv2d_fn( %input : tensor<*xi8>, %filter : tensor<*xi8>, %input_scale : tensor<*xf32>, %input_zp : tensor<*xi32>,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Mar 03 15:43:38 UTC 2023 - 12.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/replace_cast_hacks_with_tf_xla_ops.cc
// Input: [N, H, W, C] for Conv2D or [N, D, H, W, C] for Conv3D. dnums.set_input_batch_dimension(0); dnums.set_input_feature_dimension(num_dims - 1); // Kernel: [K, K, I, O] for Conv2D or [K, K, K, I, O] for Conv3D. dnums.set_kernel_input_feature_dimension(num_dims - 2); dnums.set_kernel_output_feature_dimension(num_dims - 1); // Output: [N, H, W, C] for Conv2D or [N, D, H, W, C] for Conv3D.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 47.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/prepare_patterns.td
(UpdateShapeWithAxis<-1> $qtype, $old_value))), [(CanUpdateShapeWithAxis<-1> $qtype, $old_value)]>; // The axis is set to 0 because the transpose is from the legalization of // tf.conv2d and the new channel axis is the first dimension. def ReorderTransposeDequantQuantUsedByConv : Pat<(TF_TransposeOp:$old_value (TFL_DequantizeOp (TFL_QuantizeOp $input, $qtype)), $perm),
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 30 00:40:15 UTC 2024 - 10.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/quantize_composite_functions_weight_only.mlir
%conv = "tf.Conv2D"(%arg0, %arg1) {attr_map = "0:strides,1:use_cudnn_on_gpu,2:padding,3:explicit_paddings,4:dilations", data_format = "NHWC", device = "", dilations = [1, 2, 2, 1], explicit_paddings = [], padding = "SAME", strides = [1, 1, 2, 1], use_cudnn_on_gpu = true} : (tensor<1x2x2x3xf32>, tensor<2x3x3x2xf32>) -> tensor<*xf32> return %conv : tensor<*xf32> }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 11.3K bytes - Viewed (0)