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Results 31 - 40 of 48 for 16x1xi32 (0.1 sec)
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tensorflow/compiler/mlir/tensorflow/tests/group_by_dialect.mlir
%one = "glue.constant"() { value = 1: i32 } : () -> i32 %done = "glue.compare" (%one, %one) { predicate = #glue<"compare LTE"> } : (i32, i32) -> i1 %2 = mhlo.constant dense<[[1.1]]> : tensor<1x1xf32> %3 = mhlo.multiply %2, %2 : tensor<1x1xf32> %cst = "tf.Const"() {value = dense<0.0> : tensor<f32>} : () -> tensor<f32> %0 = "tf.AddV2"(%arg0, %cst) {device = "/device:CPU:0"} : (tensor<f32>, tensor<f32>) -> tensor<f32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Sep 28 23:43:21 UTC 2022 - 5.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/tfl_legalize_hlo.mlir
// CHECK: %5 = "tfl.arg_max"(%arg0, %cst) : (tensor<1x32x1xf32>, tensor<1xi32>) -> tensor<1x1xi32> // CHECK: return %4, %5 : tensor<1x1xf32>, tensor<1x1xi32> } // CHECK-LABEL: func @convert_pytorch_argmax func.func @convert_pytorch_argmax(%arg0: tensor<1x9xi32>) -> tensor<1xi32> { %0 = mhlo.constant dense<0> : 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/shape-inference.mlir
func.func @testReshapeShapeInference(%arg0: tensor<3x4xi32>) -> tensor<*xi32> { %cst = arith.constant dense<[1, 6, 2]> : tensor<3xi32> // CHECK: "tfl.reshape"(%arg0, %cst) : (tensor<3x4xi32>, tensor<3xi32>) -> tensor<1x6x2xi32> %0 = "tfl.reshape"(%arg0, %cst) : (tensor<3x4xi32>, tensor<3xi32>) -> tensor<*xi32> func.return %0 : tensor<*xi32> } } // ----- // CHECK-LABEL: testReshapeShapeInferenceUnknownDim
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 11.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-composite-functions-tf.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 122.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/flatbuffer2mlir/vhlo.mlir
"vhlo.return_v1"(%lhs) : (tensor<f32>) -> () }): (tensor<200x100x300xf32>, tensor<10x2xi32>, tensor<10x300xf32>) -> tensor<200x100x300xf32> func.return %0 : tensor<200x100x300xf32> } // CHECK-LABEL: func.func private @scatter(%arg0: tensor<200x100x300xf32>, %arg1: tensor<10x2xi32>, %arg2: tensor<10x300xf32>) -> tensor<200x100x300xf32> {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Mar 14 19:15:40 UTC 2024 - 31.9K bytes - Viewed (1) -
tensorflow/compiler/mlir/tensorflow/tests/mlprogram.mlir
// CHECK-LABEL @lowers_string_ops // CHECK-DAG: ml_program.global public @vars.Variable_1([]) : tensor<!tf_type.string> func.func @lowers_string_ops(%arg0: tensor<128xi32>, %arg1: tensor<128xi32>, %arg2: tensor<128x1xi32>, %arg3: tensor<128x90xi32>, %arg4: tensor<128x90xi32>, %arg5: tensor<128x90xi32>, %arg6: tensor<128x90x64xf32>, %arg7: tensor<128x90x64xf32>) -> tensor<!tf_type.string> {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Feb 22 19:27:16 UTC 2024 - 7.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/components/post_calibration_component.mlir
// Note: Argument quantization sequence omitted. // CHECK: stablehlo.dot_general %{{.+}}, %{{.+}}, contracting_dims = [1] x [0] : (tensor<1x1024xi8>, tensor<1024x3xi8>) -> tensor<1x3xi32> // Note: Result dequantization sequence omitted. // CHECK: return %{{.+}} : tensor<1x3xf32> // ----- // Tests that a simple dot_general (lifted as a function) with CustomAggregators
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 01:09:50 UTC 2024 - 6.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/transforms/tf_passes.td
```mlir %0 = "tf.Const"() {value = dense<[[42.0]]> : tensor<1x1xf32>} : () -> tensor<1x1xf32> %1 = "tf.Const"() {device = "", value = dense<[[42.0]]> : tensor<1x1xf32>} : () -> tensor<1x1xf32> %2 = "tf.Const"() {device = "baz", value = dense<[[42.0]]> : tensor<1x1xf32>} : () -> tensor<1x1xf32> ``` then running this pass with 'default-device=foobar', we get: ```mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 21:18:05 UTC 2024 - 99.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/decompose_resource_ops.mlir
// CHECK-DAG: [[READ:%.+]] = "tf.ReadVariableOp"([[VAR]]) // CHECK: [[EXPAND:%.+]] = "tf.ExpandDims"([[INDEX]], [[CST]]) : (tensor<2x?xi32>, tensor<i32>) -> tensor<2x?x1xi32> // CHECK: [[TENSOR:%.+]] = "tf.TensorScatterAdd"([[READ]], [[EXPAND]], [[UPDATE]]) : (tensor<*xi32>, tensor<2x?x1xi32>, tensor<?x?x?xi32>) -> tensor<*xi32> // CHECK: "tf.AssignVariableOp"([[VAR]], [[TENSOR]])
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 22 19:47:48 UTC 2024 - 51.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/g3doc/_includes/tf_passes.md
For example, if we have the code ```mlir %0 = "tf.Const"() {value = dense<[[42.0]]> : tensor<1x1xf32>} : () -> tensor<1x1xf32> %1 = "tf.Const"() {device = "", value = dense<[[42.0]]> : tensor<1x1xf32>} : () -> tensor<1x1xf32> %2 = "tf.Const"() {device = "baz", value = dense<[[42.0]]> : tensor<1x1xf32>} : () -> tensor<1x1xf32> ``` then running this pass with 'default-device=foobar', we get: ```mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Aug 02 02:26:39 UTC 2023 - 96.4K bytes - Viewed (0)