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Results 1 - 5 of 5 for 1x1x1x1x4xi32 (0.16 sec)
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tensorflow/compiler/mlir/lite/tests/legalize-tf.mlir
func.func @test5DAddWithImplicitBroadcast(%arg0: tensor<1x1x1x3x1xi32>, %arg1 : tensor<1x1x1x1x4xi32>) -> tensor<1x1x1x3x4xi32> { %0 = "tf.Add"(%arg0, %arg1): (tensor<1x1x1x3x1xi32>, tensor<1x1x1x1x4xi32>) -> tensor<1x1x1x3x4xi32> func.return %0 : tensor<1x1x1x3x4xi32> // CHECK-LABEL: test5DAddWithImplicitBroadcast // CHECK: %0 = tfl.add(%arg0, %arg1) <{fused_activation_function = "NONE"}> : (tensor<1x1x1x3x1xi32>, tensor<1x1x1x1x4xi32>) -> tensor<1x1x1x3x4xi32>
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/lite/tests/ops.mlir
func.func @add_with_i32_five_dim_broadcasting(tensor<1x1x1x1x1xi32>, tensor<1xi32>) -> tensor<1x1x1x1x1xi32> { ^bb0(%arg0: tensor<1x1x1x1x1xi32>, %arg1: tensor<1xi32>): // CHECK: tfl.add(%arg0, %arg1) <{fused_activation_function = "RELU6"}> %0 = "tfl.add"(%arg0, %arg1) {fused_activation_function = "RELU6"} : (tensor<1x1x1x1x1xi32>, tensor<1xi32>) -> tensor<1x1x1x1x1xi32> func.return %0#0 : tensor<1x1x1x1x1xi32> } // -----
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jun 06 19:09:08 UTC 2024 - 189.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/uniform-quantized-stablehlo-to-tfl.mlir
func.func @conv_with_bias_and_relu_srq(%arg0: tensor<1x5x5x2x!quant.uniform<i8:f32, 2.000000e+00:0>>) -> (tensor<1x4x4x4x!quant.uniform<i8:f32, 8.000000e+00:-128>>) { %0 = stablehlo.constant() {value = dense<5> : tensor<1x1x1x4xi32>} : () -> tensor<1x1x1x4x!quant.uniform<i32:f32:3, {2.000000e+00, 2.000000e+00, 2.000000e+00, 2.000000e+00}>>
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/tensorflow/tests/tf-ops.mlir
func.func @testAvgPoolWrongDataType(tensor<1x7x7x16xi32>) -> tensor<1x1x1x16xi32> { ^bb0(%arg0: tensor<1x7x7x16xi32>): // expected-error @+1 {{must be tensor of floating-point values}} %0 = "tf.AvgPool"(%arg0) {T = "tfdtype$DT_INT", data_format = "NHWC", ksize = [1, 7, 7, 1], padding = "VALID", strides = [1, 1, 1, 1]} : (tensor<1x7x7x16xi32>) -> tensor<1x1x1x16xi32> func.return %0 : tensor<1x1x1x16xi32> } // -----
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 23 14:40:35 UTC 2023 - 236.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/shape_inference.mlir
func.func @simple_folding(%arg0: tensor<1x1x1x1xi32>, %arg1: tensor<1x1x1x1xf32>) -> tensor<?x?x?x?xf32> { // CHECK: %[[SHAPE:.*]] = "tf.Shape" // CHECK: %[[CONV:.*]] = "tf.Conv2DBackpropInput"(%[[SHAPE]] // CHECK-SAME: (tensor<4xi32>, tensor<1x1x1x1xf32>, tensor<1x1x1x1xf32>) -> tensor<1x1x1x1xf32> // CHECK: return %[[CONV]] : tensor<1x1x1x1xf32> %0 = "tf.Shape"(%arg0) : (tensor<1x1x1x1xi32>) -> tensor<4xi32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jan 23 17:24:10 UTC 2024 - 167.4K bytes - Viewed (0)