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Results 91 - 100 of 185 for conv2 (0.23 sec)
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tensorflow/compiler/mlir/lite/tests/optimize_functional_ops.mlir
// Verify unused if with functions without side-effects is removed. // CHECK-LABEL: main func.func @main(%arg0: tensor<3x15x14x3xf32>) -> tensor<3x15x14x8xf32> attributes {tf.entry_function = {inputs = "input", outputs = "Conv2D"}} { %cst = arith.constant dense<[0, 1, 2, 3]> : tensor<4xi32> %cst_0 = arith.constant dense<1.000000e+00> : tensor<f32> %cst_1 = arith.constant dense<0.000000e+00> : tensor<8xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Mar 30 10:34:48 UTC 2022 - 8.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/debuginfo/v1_1.0_224_frozen.wrong_attr.stack.part.pbtxt
} } attr { key: "_class" value { list { s: "loc:@MobilenetV1/Conv2d_0/weights" } } } } node { name: "MobilenetV1/MobilenetV1/Conv2d_0/Conv2D" op: "Conv2D" input: "input" input: "MobilenetV1/Conv2d_0/weights/read" attr { key: "T" value { type: DT_FLOAT } } attr { key: "data_format" value {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jul 27 18:59:05 UTC 2023 - 16.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/insert_custom_aggregation_ops.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 10 04:07:09 UTC 2024 - 32.1K bytes - Viewed (0) -
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)