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Results 1 - 9 of 9 for 1x0xf32 (0.52 sec)
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tensorflow/compiler/mlir/lite/tests/prepare-composite-functions-tf.mlir
// CHECK: }) : (tensor<1x?xf32>, tensor<1x0xf32>, tensor<1x0xf32>, tensor<1x0xf32>, tensor<1x0xf32>, tensor<1x3xf32>, tensor<1x3xf32>, tensor<1x3xf32>, tensor<1x3xf32>, none, none, none, tensor<1xf32>, tensor<1xf32>, tensor<1xf32>, tensor<1xf32>, tensor<3x1xf32>, tensor<3xf32>, tensor<1x3xf32>, tensor<1x1xf32>, tensor<1xf32>, tensor<1xf32>, tensor<1xf32>, tensor<1xf32>) -> tensor<1x3xf32>
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/tensorflow/tests/canonicalize.mlir
%3 = "tf.AddV2"(%arg0, %0): (tensor<4x4xf32>, tensor<1xf32>) -> tensor<4x4xf32> %4 = "tf.Log"(%3) {device = "/job:localhost/replica:0/task:0/device:GPU:0"}: (tensor<4x4xf32>) -> tensor<4x4xf32> // CHECK: %[[ADD1:.*]] = "tf.AddV2" // CHECK: %[[LOG1:.*]] = "tf.Log"(%[[ADD1]]) %5 = "tf.AddV2"(%4, %1): (tensor<4x4xf32>, tensor<1xf32>) -> tensor<4x4xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 09 22:07:10 UTC 2024 - 132.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/legalize-tf.mlir
func.return %8#2 : tensor<28x1x8xf32> } // CHECK-LABEL: func @LstmWithProjection(
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
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/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/lite/stablehlo/tests/uniform-quantized-stablehlo-to-tfl.mlir
func.func @select_float(%arg0: tensor<1x3xi1>, %arg1: tensor<1x3xf32>, %arg2: tensor<1x3xf32>) -> tensor<1x3xf32> { %0 = "stablehlo.select"(%arg0, %arg1, %arg2) : (tensor<1x3xi1>, tensor<1x3xf32>, tensor<1x3xf32>) -> tensor<1x3xf32> return %0 : tensor<1x3xf32> } // CHECK-LABEL: select_float // CHECK-NOT: tfl.select_v2 // CHECK: stablehlo.select // -----
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
// CHECK-LABEL: func @testLeakyRelu(%arg0: tensor<16xf32>) func.func @testLeakyRelu(tensor<16xf32>) -> tensor<16xf32> { ^bb0(%arg0: tensor<16xf32>): %0 = "tf.LeakyRelu"(%arg0) {alpha = 0.2 : f32} : (tensor<16xf32>) -> tensor<16xf32> func.return %0 : tensor<16xf32> } // ----- func.func @testLeakyWrongAlphaType(tensor<16xf32>) -> tensor<16xf32> { ^bb0(%arg0: tensor<16xf32>):
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_chain_with_broadcast(%arg0: tensor<1xf32>, %arg1: tensor<10xf32>) -> tensor<?xf32> { // CHECK: %[[MUL:.*]] = "tf.Mul"{{.*}} (tensor<1xf32>, tensor<10xf32>) -> tensor<10xf32> // CHECK: %[[ADD:.*]] = "tf.Add"(%[[MUL]], %[[MUL]]) : (tensor<10xf32>, tensor<10xf32>) -> tensor<10xf32> // CHECK: %[[CAST:.*]] = "tf.Cast"(%[[ADD]]) {{.*}} : (tensor<10xf32>) -> 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/transforms/shape_inference.cc
} else { // Recurse on the subtypes in the variant/resource. Basically if the input // were: // tensor<!tf_type.variant<tensor<?x8xf32>>> // and: // tensor<!tf_type.variant<tensor<10x8xf32>>> // we'll try here to refine tensor<?x8xf32> with tensor<10x8xf32>. auto refined_subtype = mlir::cast<TensorType>( TypeMeet(lhs_element_type_with_subtype.GetSubtypes().front(),
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Jun 08 07:28:49 UTC 2024 - 134.1K bytes - Viewed (0)