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Results 31 - 40 of 76 for conv2 (0.12 sec)
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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/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/passes/lift_quantizable_spots_as_functions.cc
} else if (function_name.contains("conv2d")) { // For Conv2D, the channel dimension must be static to calculate the // feature group count. if (!HasStaticShapeAtDims(call_op->getOperand(0), /*dims=*/3)) { return absl::InternalError( "The channel dimension of Conv2D is required to be static."); } } else if (function_name.contains("conv3d")) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 10 04:07:09 UTC 2024 - 16.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/uniform-quantized-stablehlo-to-tfl.mlir
// CHECK: %[[CONV:.+]] = stablehlo.convolution(%[[ARG0]], %[[DQ]]) // CHECK{LITERAL}: dim_numbers = [b, 0, 1, f]x[o, 0, 1, i]->[b, 0, 1, f], window = {pad = [[1, 1], [1, 1]]} {batch_group_count = 1 : i64, feature_group_count = 1 : i64} // CHECK-SAME: (tensor<1x3x3x4xf32>, tensor<2x3x3x4xf32>) -> tensor<1x3x3x2xf32> // CHECK: return %[[CONV]] // -----
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 14 17:10:32 UTC 2024 - 106.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/utils/arithmetic_count_util.h
if (!input_type || !input_type.hasStaticShape()) { return false; } total_count += input_type.getNumElements(); } *count = total_count; return true; } // For conv2d/depthwise_conv/fully_connected ops. // This algorithm actually comes from TOCO tooling_util.cc static bool GetArithmeticCountForConvAndFullyconnectedOp(mlir::Operation* op,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 3.1K bytes - Viewed (0) -
src/compress/gzip/issue14937_test.go
// has a zero MTIME. This is a requirement for the Debian maintainers // to be able to have deterministic packages. // // To patch a .gz file, use the following command: // // $ dd if=/dev/zero bs=1 seek=4 count=4 conv=notrunc of=filename.gz // // See https://golang.org/issue/14937. func TestGZIPFilesHaveZeroMTimes(t *testing.T) { // To avoid spurious false positives due to untracked GZIP files that
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Wed Apr 10 16:37:53 UTC 2024 - 2K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/quantize_xla.mlir
%conv = "tf.Conv2D"(%dq_input, %dq_weight) {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 = "VALID", 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 May 08 19:32:28 UTC 2024 - 11.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/quantize_preprocess.cc
mlir::mhlo::createLegalizeDotToDotGeneralPass()); // Unfuse mhlo BatchNorm to primitive ops. pm.addNestedPass<mlir::func::FuncOp>(mlir::odml::createUnfuseBatchNormPass()); // Fuse Conv + Mul to Conv. pm.addNestedPass<mlir::func::FuncOp>(mlir::odml::createFuseConvolutionPass()); // Fold broadcast_in_dim + Mul. pm.addNestedPass<mlir::func::FuncOp>(mlir::odml::createFoldBroadcastPass());
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Apr 24 12:49:45 UTC 2024 - 9.8K bytes - Viewed (0)