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Results 11 - 20 of 20 for 3x3x2x16xf32 (0.4 sec)
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tensorflow/compiler/mlir/quantization/tensorflow/tests/fake_quant_e2e_xla.mlir
%dimension = "tf.Const"() { value = dense<3> : tensor<1xi64> } : () -> tensor<1xi64> %6 = "tf.Sum"(%3, %dimension) { keep_dims = true }: (tensor<1x3x2x2xf32>, tensor<1xi64>) -> tensor<1x3x2x1xf32> return %5, %6 : tensor<1x3x2x2xf32>, tensor<1x3x2x1xf32> } // CHECK-LABEL: func @conv_with_multiple_uses // CHECK: %[[div:.*]] = "tf.Div"(%arg0 // CHECK: %[[add:.*]] = "tf.AddV2"(%[[div]] // CHECK: %[[maximum:.*]] = "tf.Maximum"(%[[add]]
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 7.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/legalize_hlo.mlir
%0 = "mhlo.broadcast_in_dim"(%arg0) <{broadcast_dimensions = dense<[1, 2, 3]> : tensor<3xi64>, name = "broadcast.0"}> : (tensor<8x1x16xf32>) -> tensor<3x8x8x16xf32> func.return %0 : tensor<3x8x8x16xf32> } // CHECK-LABEL: func @broadcast_in_dim_general_case( // CHECK-SAME: %[[VAL_0:.*]]: tensor<3x1x16xf32>) -> tensor<3x8x8x16xf32> {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 29 07:26:59 UTC 2024 - 340.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/optimize.mlir
%cst_3 = "tf.Const"() {value = dense<[[[[1.400000e+01]], [[-2.800000e+01]], [[4.200000e+01]]], [[[-5.600000e+01]], [[7.100000e+01]], [[-8.500000e+01]]], [[[9.900000e+01]], [[-1.130000e+02]], [[1.270000e+02]]]]> : tensor<3x3x1x1xf32>} : () -> tensor<3x3x1x1xf32> %cst_4 = "tf.Const"() {value = dense<-1.280000e+02> : tensor<f32>} : () -> tensor<f32> %cst_5 = "tf.Const"() {value = dense<0.00118110236> : tensor<1xf32>} : () -> tensor<1xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 8.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/legalize-tf.mlir
%0 = "tf.Less"(%arg0, %arg1) : (tensor<8x7x6x5x?x3x2x1xf32>, tensor<?x3x2x1xf32>) -> tensor<8x7x6x5x?x3x2x1xi1> %1 = "tf.SelectV2"(%0, %arg0, %arg1) : (tensor<8x7x6x5x?x3x2x1xi1>, tensor<8x7x6x5x?x3x2x1xf32>, tensor<?x3x2x1xf32>) -> tensor<8x7x6x5x?x3x2x1xf32> func.return %1 : tensor<8x7x6x5x?x3x2x1xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 05 01:54:33 UTC 2024 - 153.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/bridge/optimize.mlir
return %2 : tensor<?x2x2x1xi8> } // ----- // CHECK-LABEL: func @convolution_add_add_f32 func.func @convolution_add_add_f32( %lhs: tensor<?x3x2x1xf32>, %rhs: tensor<2x1x1x1xf32>, %zp_offset: tensor<?x2x2x1xf32>, %bias: tensor<1xf32> ) -> tensor<?x2x2x1xf32> { // CHECK-DAG: %[[conv:.*]] = mhlo.convolution
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Feb 24 02:26:47 UTC 2024 - 10.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/quantize_composite_functions.mlir
// CHECK: Number of dequantize layers added: 1 } // ----- module { func.func @float_einsum(%arg0: tensor<?x64x32xf32>, %arg1: tensor<32x2x16xf32>) -> (tensor<?x64x2x16xf32>) { %0 = "tf.Einsum"(%arg0, %arg1) {equation = "abc,cde->abde"} : (tensor<?x64x32xf32>, tensor<32x2x16xf32>) -> tensor<?x64x2x16xf32> func.return %0 : tensor<?x64x2x16xf32> } // CHECK-LABEL: func @float_einsum
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Nov 06 01:23:21 UTC 2023 - 15.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/shape_inference.mlir
func.func @conv2d_partially_dynamic_spatial_dim(%arg0: tensor<256x?x32x3xf32>, %arg1: tensor<3x3x3x16xf32>) -> tensor<*xf32> { // CHECK: "tf.Conv2D" // CHECK-SAME: -> tensor<256x?x32x16xf32> %0 = "tf.Conv2D"(%arg0, %arg1) {padding = "SAME", strides = [1, 1, 1, 1]} : (tensor<256x?x32x3xf32>, tensor<3x3x3x16xf32>) -> tensor<*xf32> func.return %0 : tensor<*xf32> }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jan 23 17:24:10 UTC 2024 - 167.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/constant-fold.mlir
%0 = "tf.Const"() {value = dense<0.111111112> : tensor<3x3x1x1xf32>} : () -> tensor<3x3x1x1xf32> %1 = "tf.Const"() {value = dense<1.000000e+00> : tensor<1x520x520x1xf32>} : () -> tensor<1x520x520x1xf32> %2 = "tf.DepthwiseConv2dNative"(%1, %0) {data_format = "NHWC", device = "", dilations = [1, 1, 1, 1], explicit_paddings = [], padding = "SAME", strides = [1, 1, 1, 1]} : (tensor<1x520x520x1xf32>, tensor<3x3x1x1xf32>) -> tensor<1x520x520x1xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jan 31 23:22:24 UTC 2024 - 36.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/tests/legalize-tf.mlir
// CHECK: mhlo.convolution(%arg0, %arg1) // CHECK-SAME{LITERAL}: pad = [[6, 0], [3, 3]] %0 = "tf.Conv2D"(%arg0, %arg1) {data_format = "NHWC", dilations = [1, 2, 3, 1], padding = "EXPLICIT", explicit_paddings = [0, 0, 6, 0, 3, 3, 0, 0], strides = [1, 4, 5, 1]} : (tensor<256x32x32x6xf32>, tensor<3x3x3x16xf32>) -> tensor<256x9x7x16xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon May 06 18:46:23 UTC 2024 - 335.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/optimize.mlir
func.return %1 : tensor<256x30x30x16xf32> // CHECK-DAG: %[[w:.*]] = arith.constant dense<1.000000e+00> : tensor<3x3x3x16xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 16 20:31:41 UTC 2024 - 284.1K bytes - Viewed (0)