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Results 11 - 20 of 33 for 448xi32 (0.13 sec)
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tensorflow/compiler/mlir/lite/quantization/tensorflow/tests/fallback_to_flex_ops_legacy.mlir
} // CHECK-LABEL: conv2d_backprop_input_with_add func.func @conv2d_backprop_input_with_add(%arg0: tensor<4xi32>, %arg1: tensor<3x3x1x32xf32>, %arg2: tensor<15x14x14x32xf32>) -> tensor<15x28x28x1xf32> { %0 = "tf.Conv2DBackpropInput"(%arg0, %arg1, %arg2) {strides = [1, 2, 2, 1], padding="SAME", dilations=[1, 1, 1, 1]}: (tensor<4xi32>, tensor<3x3x1x32xf32>, tensor<15x14x14x32xf32>) -> tensor<15x28x28x1xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 5.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/flatbuffer2mlir/custom_op.mlir
func.func @main(%arg0: tensor<32x4x4x128xf32>, %arg1: tensor<1x32x42x128xf32>, %arg2: tensor<4xi32>) -> tensor<1x64x84x32xf32> { %0 = "tfl.custom"(%arg0, %arg1, %arg2) {custom_code = "Convolution2DTransposeBias", custom_option = #tfl<const_bytes : "0x010000000200000002000000">} : (tensor<32x4x4x128xf32>, tensor<1x32x42x128xf32>, tensor<4xi32>) -> tensor<1x64x84x32xf32> func.return %0 : tensor<1x64x84x32xf32> } // CHECK-LABEL: main
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 827 bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/flatbuffer2mlir/custom_op_offset.mlir
func.func @main(%arg0: tensor<32x4x4x128xf32>, %arg1: tensor<1x32x42x128xf32>, %arg2: tensor<4xi32>) -> tensor<1x64x84x32xf32> { %0 = "tfl.custom"(%arg0, %arg1, %arg2) {custom_code = "Convolution2DTransposeBias", custom_option = #tfl<const_bytes : "0x010000000200000002000000">} : (tensor<32x4x4x128xf32>, tensor<1x32x42x128xf32>, tensor<4xi32>) -> tensor<1x64x84x32xf32> func.return %0 : tensor<1x64x84x32xf32> } // CHECK-LABEL: main
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 847 bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/optimize_batch_matmul.mlir
// CHECK: %[[RES1:.*]] = "tfl.batch_matmul"(%[[RES0]], %arg2) <{adj_x = false, adj_y = false, asymmetric_quantize_inputs = false}> : (tensor<8x4xf32>, tensor<4x256xf32>) -> tensor<8x256xf32> %2 = "tfl.batch_matmul"(%1, %arg2) {adj_x = true, adj_y = false, asymmetric_quantize_inputs = false} : (tensor<4x8xf32>, tensor<4x256xf32>) -> tensor<8x256xf32> func.return %2 : tensor<8x256xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/tensorflow/tests/fallback_to_flex_ops_default.mlir
} // CHECK-LABEL: conv2d_backprop_input_with_add func.func @conv2d_backprop_input_with_add(%arg0: tensor<4xi32>, %arg1: tensor<3x3x1x32xf32>, %arg2: tensor<15x14x14x32xf32>) -> tensor<15x28x28x1xf32> { %0 = "tf.Conv2DBackpropInput"(%arg0, %arg1, %arg2) {strides = [1, 2, 2, 1], padding="SAME", dilations=[1, 1, 1, 1]}: (tensor<4xi32>, tensor<3x3x1x32xf32>, tensor<15x14x14x32xf32>) -> tensor<15x28x28x1xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 13.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/canonicalize.mlir
// CHECK-LABEL: broadcast_to_to_reshape 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> }
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/lite/stablehlo/tests/tfl_legalize_hlo.mlir
// CHECK-NEXT: %14 = "tfl.pseudo_const"() <{value = dense<[-1, -1, 0, -1]> : tensor<4xi32>}> : () -> tensor<4xi32> // CHECK-NEXT: %15 = "tfl.pseudo_const"() <{value = dense<[-1, -1, -1, 0]> : tensor<4xi32>}> : () -> tensor<4xi32> // CHECK-NEXT: %16 = "tfl.pseudo_const"() <{value = dense<1> : tensor<i32>}> : () -> tensor<i32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 40.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/flatbuffer2mlir/constants.mlir
func.return %0 : tensor<4xi16> } func.func @i32() -> tensor<4xi32> { // CHECK-LABEL: @i32 // CHECK: value = dense<[1, 2, 3, 16909060]> : tensor<4xi32> // Check bytes come back in the right order %0 = "tfl.pseudo_const" () { value = dense<[1, 2, 3, 16909060]> : tensor<4xi32> } : () -> tensor<4xi32> func.return %0 : tensor<4xi32> } func.func @i64() -> tensor<4xi64> { // CHECK-LABEL: @i64
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 12.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/tac/tests/fold-constants-to-subgraph.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 10.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/transforms/hlo_matchers.cc
} return true; } // Matches %iota generated from the following code (rank 3 example): // // %iota_r1 = "mhlo.iota"(){iota_dimension = 0 : i32} : () -> tensor<44xi32> // %iota = "mhlo.reshape"(%iota_r1): (tensor<44xi32>) -> tensor<1x1x44xi32> // // Where $dimensions is of size 1 and $dimensions[0] = 2. // // In general matches a 1-D Iota with multiple dimensions of size 1 added // through a reshape.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 11.6K bytes - Viewed (0)