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Results 121 - 130 of 232 for stride_w (0.2 sec)
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tensorflow/compiler/mlir/tensorflow/tests/tf_optimize.mlir
%cst2 = arith.constant dense<[1.0, 2.0]> : tensor<2xf32> %0 = "tf.Conv2D"(%arg0, %cst0) {T = "tfdtype$DT_FLOAT", data_format = "NHWC", dilations = [1, 2, 3, 1], padding = "SAME", strides = [1, 4, 5, 1]} : (tensor<1x112x112x3xf32>, tensor<1x3x3x2xf32>) -> tensor<1x28x23x2xf32> %1 = "tf.Mul"(%0, %cst2) : (tensor<1x28x23x2xf32>, tensor<2xf32>) -> tensor<1x28x23x2xf32> func.return %1 : tensor<1x28x23x2xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 9.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/tensorflow/tests/tf_to_quant.mlir
%rst = "tf.Conv2D"(%arg, %fq) {T = "tfdtype$DT_FLOAT", data_format = "NHWC", dilations = [1, 2, 3, 1], padding = "SAME", strides = [1, 4, 5, 1]} : (tensor<256x32x32x3xf32>, tensor<3x3x3x16xf32>) -> tensor<256x8x7x16xf32> func.return %rst : tensor<256x8x7x16xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 9.5K bytes - Viewed (0) -
src/image/jpeg/scan.go
b[unzig[zig]] *= qt[zig] } idct(b) dst, stride := []byte(nil), 0 if d.nComp == 1 { dst, stride = d.img1.Pix[8*(by*d.img1.Stride+bx):], d.img1.Stride } else { switch compIndex { case 0: dst, stride = d.img3.Y[8*(by*d.img3.YStride+bx):], d.img3.YStride case 1: dst, stride = d.img3.Cb[8*(by*d.img3.CStride+bx):], d.img3.CStride case 2: dst, stride = d.img3.Cr[8*(by*d.img3.CStride+bx):], d.img3.CStride
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Thu Apr 25 00:46:29 UTC 2024 - 15.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/components/tf_to_stablehlo.mlir
%cst_2 = "tf.Const"() {value = dense<[0.3, 0.4]> : tensor<2xf32>} : () -> tensor<2xf32> %0 = "tf.Conv2D"(%arg_0, %cst_0) {data_format = "NHWC", dilations = [1, 1, 2, 1], explicit_paddings = [], padding = "SAME", strides = [1, 1, 2, 1], use_cudnn_on_gpu = true} : (tensor<1x3x4x3xf32>, tensor<2x3x3x2xf32>) -> tensor<1x3x2x2xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Apr 08 20:05:12 UTC 2024 - 13.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/utils/perception_ops_utils_test.cc
fields.emplace_back(pool_size_id, pool_size); auto strides_id = ::mlir::StringAttr::get(context, "strides"); fields.emplace_back(strides_id, strides); DictionaryAttr dict = DictionaryAttr::get(context, fields); return TF::FuncAttr::get(context, "MaxUnpooling2D", dict); } } // namespace class PerceptionUtilsTest : public ::testing::Test { protected: PerceptionUtilsTest() {}
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Sep 29 21:02:21 UTC 2022 - 7.4K bytes - Viewed (0) -
src/encoding/hex/hex_test.go
} } } func TestDumper(t *testing.T) { var in [40]byte for i := range in { in[i] = byte(i + 30) } for stride := 1; stride < len(in); stride++ { var out bytes.Buffer dumper := Dumper(&out) done := 0 for done < len(in) { todo := done + stride if todo > len(in) { todo = len(in) } dumper.Write(in[done:todo]) done = todo } dumper.Close()
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Wed May 08 19:30:23 UTC 2024 - 7.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/replace_cast_hacks_with_tf_xla_ops.cc
emitError(loc, "zero point is expected to be a constant with a single value"); return {}; } if (strides.size() != num_dims || dilations.size() != num_dims) { emitError(loc, absl::StrFormat( "strides and dilations are expected to be %d-element arrays", num_dims)); return {}; } xla::ConvolutionDimensionNumbers dnums;
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/stablehlo/tests/tf-tfl-translate-serialize-stablehlo-conv.mlir
module { func.func @main(%arg0: tensor<4x68x68x3xf32>, %arg1: tensor<5x5x3x8xf32>) -> tensor<4x64x64x8xf32> { %0 = "tf.Conv2D"(%arg0, %arg1) {padding = "VALID", strides = [1, 1, 1, 1]} : (tensor<4x68x68x3xf32>, tensor<5x5x3x8xf32>) -> tensor<4x64x64x8xf32> func.return %0 : tensor<4x64x64x8xf32> }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Feb 27 23:35:37 UTC 2023 - 425 bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/prepare_quantize_ptq_per_channel.mlir
%2 = "tf.Conv2D"(%1, %0) {attr_map = "0:strides,1:use_cudnn_on_gpu,2:padding,3:explicit_paddings,4:dilations", data_format = "NHWC", device = "", dilations = [1, 1, 1, 1], explicit_paddings = [], padding = "SAME", strides = [1, 1, 2, 1], use_cudnn_on_gpu = true} : (tensor<1x3x4x3xf32>, tensor<2x3x3x2xf32>) -> tensor<*xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Feb 01 10:21:29 UTC 2023 - 4.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/optimize.mlir
%bias = arith.constant dense<3.0> : tensor<16xf32> %value = arith.constant dense<4.0> : tensor<16xf32> %0 = "tf.Conv2D"(%arg, %filter) {T = "tfdtype$DT_FLOAT", data_format = "NHWC", dilations = [1, 2, 3, 1], padding = "SAME", strides = [1, 4, 5, 1]} : (tensor<256x32x32x3xf32>, tensor<3x3x3x16xf32>) -> tensor<256x8x7x16xf32> %1 = "tf.BiasAdd"(%0, %bias) {T = "tfdtype$DT_FLOAT", data_format = "NHWC"}: (tensor<256x8x7x16xf32>, tensor<16xf32>) -> tensor<256x8x7x16xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Jan 05 18:35:42 UTC 2024 - 3.3K bytes - Viewed (0)