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Results 41 - 50 of 62 for 2x3x4x4xf32 (0.14 sec)
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tensorflow/compiler/mlir/quantization/tensorflow/tests/quantize_composite_functions_drq.mlir
module { func.func @depthwise_conv(%arg0: tensor<1x3x4x3xf32>) -> (tensor<*xf32>, tensor<*xf32>) { %cst_0 = "tf.Const"() {value = dense<0.000000e+00> : tensor<3xf32>} : () -> tensor<3xf32> %cst_1 = "tf.Const"() {value = dense<3.000000e+00> : tensor<2x3x3x1xf32>} : () -> tensor<2x3x3x1xf32> %cst_2 = "tf.Const"() {value = dense<3.000000e+00> : tensor<2x3x3x2xf32>} : () -> tensor<2x3x3x2xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Jan 05 18:35:42 UTC 2024 - 9.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/lift_quantizable_spots_as_functions_xla.mlir
%0 = "tf.DepthwiseConv2dNative"(%arg0, %cst_0) {data_format = "NHWC", dilations = [1, 1, 1, 1], explicit_paddings = [], padding = "SAME", strides = [1, 2, 2, 1]} : (tensor<1x3x4x3xf32>, tensor<2x3x3x1xf32>) -> tensor<1x2x2x3xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 8.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/canonicalize.mlir
func.func @broadcast_to_to_reshape(%arg0: tensor<4x4x4xf32>, %arg1 : tensor<4xi32>) -> tensor<1x4x4x4xf32> { %0 = "tfl.broadcast_to"(%arg0, %arg1) : (tensor<4x4x4xf32>, tensor<4xi32>) -> tensor<1x4x4x4xf32> // CHECK: "tfl.reshape" // CHECK-SAME: (tensor<4x4x4xf32>, tensor<4xi32>) -> tensor<1x4x4x4xf32> func.return %0 : tensor<1x4x4x4xf32> } // Converts tfl.broadcast_to to tfl.reshape if input and output have the same
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 20.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/lift_quantizable_spots_as_functions_drq.mlir
} // ----- // CHECK-LABEL: lift_float_conv func.func @lift_float_conv(%arg0: tensor<1x3x4x3xf32>) -> (tensor<*xf32>, tensor<*xf32>) { %cst = "tf.Const"() {value = dense<0.000000e+00> : tensor<2xf32>} : () -> tensor<2xf32> %cst_1 = "tf.Const"() {value = dense<3.000000e+00> : tensor<2x3x3x2xf32>} : () -> tensor<2x3x3x2xf32> %0 = "tf.Conv2D"(%arg0, %cst_1) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 11.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/prepare_quantize_ptq.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Feb 01 10:21:29 UTC 2023 - 9.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-tf-with-allowing-bf16-and-f16-type-legalization.mlir
func.func @depthwise_conv_2d_bf16(%arg0 : tensor<256x32x32x3xbf16>, %arg1 : tensor<3x3x3x4xf32>, %arg2 : tensor<256x3x32x32xf32>) -> tensor<256x30x30x12xbf16> { %0 = "tf.DepthwiseConv2dNative"(%arg0, %arg1) {T = "tfdtype$DT_FLOAT", data_format = "NHWC", dilations = [1, 2, 3, 1], padding = "SAME", strides = [1, 4, 5, 1]} : (tensor<256x32x32x3xbf16>, tensor<3x3x3x4xf32>) -> tensor<256x30x30x12xbf16> func.return %0 : tensor<256x30x30x12xbf16>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 26 23:53:32 UTC 2022 - 2.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/transpose-op.mlir
%2 = "tf.Transpose"(%arg0, %0) : (tensor<1x4x4x8xf32>, tensor<4xi32>) -> tensor<1x8x4x4xf32> // expected-error @+1 {{'tf.Transpose' op perm[1]=16705 must be in range [-4, 4)}} %3 = "tf.Transpose"(%2, %1) : (tensor<1x8x4x4xf32>, tensor<4xi32>) -> tensor<1x4x4x8xf32> func.return %3 : tensor<1x4x4x8xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Mar 23 05:52:37 UTC 2023 - 634 bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/pipelines/process_nchw_tensor.mlir
return %2 : tensor<1x8x4x4xf32> } // CHECK-DAG: %[[CONST:.+]] = stablehlo.constant {{.*}} : tensor<3x3x8x8xf32> // CHECK-DAG: %[[TRANSPOSE_0:.+]] = stablehlo.transpose %[[ARG]], dims = [0, 2, 3, 1] : (tensor<1x8x4x4xf32>) -> tensor<1x4x4x8xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 18 20:32:46 UTC 2024 - 12.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/quantize.mlir
func.func private @conv(%input: tensor<1x3x4x3xf32> {tf._user_specified_name = "input_tensor"}) -> tensor<*xf32> attributes {tf._construction_context = "kEagerRuntime", tf._input_shapes = [#tf_type.shape<1x3x4x3>]} { %weight = arith.constant dense_resource<__elided__> : tensor<2x3x3x2xf32> %bias = arith.constant dense<[7.11401462, 7.05456924]> : 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/quantization/tensorflow/tests/prepare_quantize_drq.mlir
%2 = "tf.BiasAdd"(%1, %cst_0) {data_format = "NHWC", device = ""} : (tensor<*xf32>, tensor<2xf32>) -> tensor<*xf32> func.return %2: tensor<*xf32> } func.func private @composite_conv2d_fn_1(%arg0: tensor<1x3x4x3xf32>, %arg1: tensor<2x3x3x512xf32>) -> tensor<*xf32> attributes {tf_quant.composite_function} {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 6.7K bytes - Viewed (0)