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Results 1 - 10 of 11 for ONE_HOT (0.23 sec)
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tensorflow/compiler/mlir/lite/experimental/tac/tests/get-alternative-subgraph.mlir
func.func private @func_10_CPU_FLOAT(%arg0: tensor<3xi32>, %arg1: tensor<i32>, %arg2: tensor<f32>, %arg3: tensor<f32>) -> tensor<*xf32> attributes {tac.device = "CPU", tac.inference_type = "FLOAT", tac.interface_name = "func_10"} { %0 = "tfl.one_hot"(%arg0, %arg1, %arg2, %arg3) {axis = -1 : i32, tac.device = "CPU", tac.inference_type = "FLOAT"} : (tensor<3xi32>, tensor<i32>, tensor<f32>, tensor<f32>) -> tensor<*xf32> func.return %0 : tensor<*xf32> }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 20.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/optimize.mlir
// CHECK: %[[RESHAPE:.*]] = "tfl.reshape"(%0, %[[CST]]) : (tensor<?x1xi32>, tensor<1xi32>) -> tensor<?xi32> // CHECK: %[[ONE_HOT:.*]] = "tfl.one_hot"(%1, %[[CST_0]], %[[CST_1]], %[[CST_2]]) <{axis = -1 : i32}> : (tensor<?xi32>, tensor<i32>, tensor<f32>, tensor<f32>) -> tensor<?x10xf32> // CHECK-NEXT: return %[[ONE_HOT]] } // CHECK-LABEL: noReplaceReshapeEqualWithOneHotDynamicNonBatch
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 16 20:31:41 UTC 2024 - 284.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/schema/schema_v3b.fbs
LOG = 73, SUM = 74, SQRT = 75, RSQRT = 76, SHAPE = 77, POW = 78, ARG_MIN = 79, FAKE_QUANT = 80, REDUCE_PROD = 81, REDUCE_MAX = 82, PACK = 83, LOGICAL_OR = 84, ONE_HOT = 85, LOGICAL_AND = 86, LOGICAL_NOT = 87, UNPACK = 88, REDUCE_MIN = 89, FLOOR_DIV = 90, REDUCE_ANY = 91, SQUARE = 92, ZEROS_LIKE = 93, FILL = 94, FLOOR_MOD = 95,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 28 14:28:27 UTC 2024 - 30K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/schema/schema.fbs
LOG = 73, SUM = 74, SQRT = 75, RSQRT = 76, SHAPE = 77, POW = 78, ARG_MIN = 79, FAKE_QUANT = 80, REDUCE_PROD = 81, REDUCE_MAX = 82, PACK = 83, LOGICAL_OR = 84, ONE_HOT = 85, LOGICAL_AND = 86, LOGICAL_NOT = 87, UNPACK = 88, REDUCE_MIN = 89, FLOOR_DIV = 90, REDUCE_ANY = 91, SQUARE = 92, ZEROS_LIKE = 93, FILL = 94, FLOOR_MOD = 95,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 03 18:01:23 UTC 2024 - 41.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/ops.mlir
func.func @testOneHot(%arg0: tensor<3xi32>, %arg1: tensor<i32>, %arg2: tensor<f32>, %arg3: tensor<f32>) -> tensor<*xf32> { // CHECK: "tfl.one_hot"(%arg0, %arg1, %arg2, %arg3) <{axis = -1 : i32}> : (tensor<3xi32>, tensor<i32>, tensor<f32>, tensor<f32>) -> tensor<*xf32> %0 = "tfl.one_hot"(%arg0, %arg1, %arg2, %arg3) {axis = -1 : i32} : (tensor<3xi32>, tensor<i32>, tensor<f32>, tensor<f32>) -> tensor<*xf32> func.return %0 : tensor<*xf32> }
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/ir/tf_generated_ops.td
depth = 3 on_value = 5.0 off_value = 0.0 axis = -1 ``` Then output is `[4 x 3]`: ``` output = [5.0 0.0 0.0] // one_hot(0) [0.0 0.0 5.0] // one_hot(2) [0.0 0.0 0.0] // one_hot(-1) [0.0 5.0 0.0] // one_hot(1) ``` Suppose that ``` indices = [0, 2, -1, 1] depth = 3 on_value = 0.0 off_value = 3.0 axis = 0 ```
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 23:24:08 UTC 2024 - 793K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/legalize-tf.mlir
%0 = "tf.OneHot"(%arg0, %arg1, %arg2, %arg3) {axis = -1 : i64} : (tensor<3xi32>, tensor<i32>, tensor<f32>, tensor<f32>) -> tensor<*xf32> func.return %0: tensor<*xf32> // CHECK-LABEL: OneHot // CHECK: "tfl.one_hot"(%arg0, %arg1, %arg2, %arg3) <{axis = -1 : i32}> : (tensor<3xi32>, tensor<i32>, tensor<f32>, tensor<f32>) -> tensor<*xf32> } func.func @argmax(%arg0: tensor<3xi32>, %arg1: tensor<i32>) -> tensor<i32> {
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/ir/tfl_ops.td
); let results = (outs TFL_TensorOf<[F32, I32, I64, QI8, QUI8, UI8, QI16]>:$output); let hasOptions = 1; let customOption = "ReducerOptions"; } def TFL_OneHotOp : TFL_Op<"one_hot", [ QuantizableResult, Pure]> { let summary = "OneHot operator"; let description = [{ Returns a one-hot tensor.The locations represented by indices in `indices`
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jun 06 19:09:08 UTC 2024 - 186K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/tests/legalize-tf.mlir
// OneHot op legalizations. //===----------------------------------------------------------------------===// // ----- // CHECK-LABEL:one_hot func.func @one_hot(%indices: tensor<3xi32>, %on_value: tensor<f32>, %off_value: tensor<f32>) -> tensor<3x5xf32> { // CHECK: %[[IOTA:.*]] = "mhlo.iota"() <{iota_dimension = 1 : i64}> : () -> tensor<3x5xi32>
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/schema/schema_generated.h
"SUM", "SQRT", "RSQRT", "SHAPE", "POW", "ARG_MIN", "FAKE_QUANT", "REDUCE_PROD", "REDUCE_MAX", "PACK", "LOGICAL_OR", "ONE_HOT", "LOGICAL_AND", "LOGICAL_NOT", "UNPACK", "REDUCE_MIN", "FLOOR_DIV", "REDUCE_ANY", "SQUARE", "ZEROS_LIKE", "FILL", "FLOOR_MOD",
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 21 18:21:50 UTC 2024 - 1M bytes - Viewed (0)