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Results 141 - 150 of 178 for conv_2d (0.12 sec)
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tensorflow/compiler/mlir/quantization/tensorflow/tests/replace_cast_hacks_with_tf_xla_ops_large_constants.mlir
%3 = "tf.Cast"(%2) {Truncate = false} : (tensor<960x960x3x512xi8>) -> tensor<960x960x3x512xi32> %4 = "tf.Sub"(%3, %arg5) : (tensor<960x960x3x512xi32>, tensor<512xi32>) -> tensor<960x960x3x512xi32> %5 = "tf.Conv2D"(%1, %4) {dilations = [1, 1, 1, 1], explicit_paddings = [], padding = "SAME", strides = [1, 1, 2, 1], use_cudnn_on_gpu = true} : (tensor<1x2240x2240x3xi32>, tensor<960x960x3x512xi32>) -> tensor<1x2240x1120x512xi32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 5.9K bytes - Viewed (0) -
test/typeparam/issue49027.dir/main.go
package main import ( "./a" "fmt" ) func main() { s := "foo" x := a.Conv(s) if x != s { panic(fmt.Sprintf("got %s wanted %s", x, s)) } y, ok := a.Conv2(s) if !ok { panic("conversion failed") } if y != s { panic(fmt.Sprintf("got %s wanted %s", y, s)) } z := a.Conv3(s) if z != s { panic(fmt.Sprintf("got %s wanted %s", z, s)) }
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Thu Mar 24 02:14:15 UTC 2022 - 617 bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/quantize.mlir
%dq_bias = "quantfork.dcast"(%q_bias) : (tensor<2x!quant.uniform<i32:f32, 0.044022349891595126>>) -> tensor<2xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 08 19:32:28 UTC 2024 - 6.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tf-ops.mlir
%0 = "tf.Conv2D"(%arg0, %arg1) {padding = "SAME", strides = [1, 1]} : (tensor<256x32x32x3xf32>, tensor<3x3x3x16xf32>) -> tensor<256x30x30x16xf32> func.return %0 : tensor<256x30x30x16xf32> } // ----- func.func @testConv2D(%arg0: tensor<256x32x32x3xf32>, %arg1: tensor<3x3x3x16xf32>) -> tensor<256x30x30x16xf32> { // expected-error @+1 {{requires positive strides}}
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 23 14:40:35 UTC 2023 - 236.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/prepare_lifting.td
def MultiplyFakeQuantValue : NativeCodeCall< "MultiplyFakeQuantValue($_builder, $_loc, $0...)">; // Convert AddV2Op following an AffineOp to BiasAddOp. // For Conv3D, even though the Conv3D op has "NDHWC" data format, the BiasAdd // will still has the data format of "NHWC". def ConvertAddToBiasAdd : Pat< (TF_AddV2Op (SupportedAffineOpMatcher $conv_out, $input, $weight),
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Feb 14 03:24:59 UTC 2024 - 8.4K bytes - Viewed (0) -
tensorflow/cc/gradients/nn_grad_test.cc
#include "tensorflow/core/lib/core/status_test_util.h" #include "tensorflow/core/lib/random/random.h" namespace tensorflow { namespace { using ops::AvgPool; using ops::AvgPool3D; using ops::BiasAdd; using ops::Conv2D; using ops::Conv2DBackpropInput; using ops::DepthwiseConv2dNative; using ops::Elu; using ops::FractionalAvgPool; using ops::FractionalMaxPool; using ops::FusedBatchNormV3; using ops::L2Loss; using ops::LogSoftmax;
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/tfr/examples/mnist/ops_defs.py
derived_attrs=['T: {float, int8}'], outputs=['o: T']) def _composite_conv_add_relu(input_, filter_, bias, stride_w, stride_h, dilation_w, dilation_h, padding, act): res = tf.raw_ops.Conv2D( input=input_, filter=filter_, strides=[1, stride_w, stride_h, 1], dilations=[1, dilation_w, dilation_h, 1], padding=padding) res = tf.raw_ops.Add(x=res, y=bias) if act == 'RELU':
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/mlir/tf2xla/tests/legalize-tf-prefer-tf2xla.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Apr 06 15:32:52 UTC 2024 - 15.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/tests/tf_to_corert/tf_to_corert_pipeline.mlir
%outputs_6, %control_7 = tf_executor.island wraps "tf.Const"() {device = "", value = dense<[-1, 16384]> : tensor<2xi32>} : () -> tensor<2xi32> %outputs_8, %control_9 = tf_executor.island wraps "tf.Conv2D"(%arg0, %outputs_0) {data_format = "NHWC", device = "", dilations = [1, 1, 1, 1], explicit_paddings = [], padding = "SAME", strides = [1, 2, 2, 1], use_cudnn_on_gpu = true} : (tensor<16x224x224x3xf32>, tensor<*xf32>) -> tensor<16x112x112x?xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 08 00:18:59 UTC 2024 - 7.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/quantized_function_library_uniform_quantized.mlir
// func.func func_name_${key1}_fn (...) { // ...${key2}... // } // ``` // The above template with generate two functions by substituting `key1` and // `key2` with given values. module { for main_op in ["Conv2D", "DepthwiseConv2D", "MatMul"] { parameters[ {"quantized_ops": ["${main_op}", "BiasAdd"], "act_func": "internal_requantize_no_activation_fn", "output_type": "!tf_type.qint8"},
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Aug 29 01:13:58 UTC 2023 - 19.3K bytes - Viewed (0)