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Results 1 - 10 of 11 for 16xi32 (0.15 sec)
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tensorflow/compiler/mlir/tensorflow/tests/tf-ops.mlir
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>): // expected-error @+1 {{attribute 'alpha' failed to satisfy constraint: 32-bit float}}
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/lite/tests/legalize-tf.mlir
// CHECK: return } func.func @addV2(%arg0: tensor<1xi32>, %arg1: tensor<1xi32>) -> tensor<1xi32> { %0 = "tf.AddV2"(%arg0, %arg1) : (tensor<1xi32>, tensor<1xi32>) -> tensor<1xi32> func.return %0 : tensor<1xi32> // CHECK-LABEL: addV2 // CHECK: tfl.add %arg0, %arg1 {fused_activation_function = "NONE"} : tensor<1xi32> } func.func @addV2I16(%arg0: tensor<1xi16>, %arg1: tensor<1xi16>) -> tensor<1xi16> {
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/tensorflow/tests/shape_inference.mlir
// CHECK-LABEL: func @main(%arg0: tensor<1xi32>, %arg1: tensor<1xi32>) -> tensor<1xi32> func.func @main(%arg0: tensor<1xi32>, %arg1: tensor<1xi32>) -> tensor<*xi32> { // CHECK: %[[RESULT:.*]] = "tf.AddV2" // CHECK-SAME: (tensor<1xi32>, tensor<1xi32>) -> tensor<1xi32> // CHECK: return %[[RESULT]] : tensor<1xi32> %0 = "tf.Cast"(%arg0) : (tensor<1xi32>) -> tensor<*xi32> %1 = "tf.Cast"(%arg1) : (tensor<1xi32>) -> tensor<*xi32>
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/lite/tests/prepare-composite-functions-tf.mlir
// CHECK: [[VAL_23:%.*]] = "tf.Reshape"([[VAL_15]]#1, [[VAL_22]]) : (tensor<1x10xf32>, tensor<1xi32>) -> tensor<10xf32> // CHECK-DAG: [[VAL_24:%.*]] = "tf.Const"() <{value = dense<-1> : tensor<1xi32>}> : () -> tensor<1xi32> // CHECK: [[VAL_25:%.*]] = "tf.Reshape"([[VAL_15]]#2, [[VAL_24]]) : (tensor<1x10xf32>, tensor<1xi32>) -> tensor<10xf32>
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
%2 = "tf.AddN"(%arg0, %1, %1) : (tensor<2xi32>, tensor<2xi32>, tensor<2xi32>) -> tensor<2xi32> %3 = "tf.AddN"(%1, %arg0, %1) : (tensor<2xi32>, tensor<2xi32> , tensor<2xi32>) -> tensor<2xi32> %4 = "tf.AddN"(%1, %1) : (tensor<2xi32>, tensor<2xi32>) -> tensor<2xi32> %5 = "tf.AddN"(%arg0, %1, %0) : (tensor<2xi32>, tensor<2xi32>, tensor<2xi32>) -> tensor<2xi32> func.return %2, %3, %4, %5: tensor<2xi32>, tensor<2xi32>, tensor<2xi32>, tensor<2xi32> }
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/ops.mlir
// ----- func.func @testFusedActivationFunction(%arg0: tensor<4xi32>, %arg1: tensor<4xi32>) -> (tensor<4xi32>, tensor<4xi32>, tensor<4xi32>, tensor<4xi32>, tensor<4xi32>, tensor<4xi32>) { // CHECK: "NONE" %0 = tfl.add %arg0, %arg1 {fused_activation_function = "NONE"} : tensor<4xi32> // CHECK: "RELU" %1 = tfl.add %arg0, %arg1 {fused_activation_function = "RELU"} : tensor<4xi32> // CHECK: "RELU_N1_TO_1"
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 %2 = "tf.A"(%arg0) : (tensor<?xi32>) -> tensor<?xi32> %3 = "tf.B"(%2) {device = "tpu0"} : (tensor<?xi32>) -> tensor<?xi32> %4 = "tf.C"(%2, %3) {device = "tpu0"} : (tensor<?xi32>, tensor<?xi32>) -> tensor<?xi32> %5 = "tf.D"(%4) : (tensor<?xi32>) -> tensor<?xi32> ``` After the pass, we will have: ```mlir %0 = "tf.A"(%arg0) : (tensor<?xi32>) -> tensor<?xi32>
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
// CHECK-DAG: %[[BROADCAST_DIM:.+]] = arith.constant dense<{{\[3, 2, 1, 1\]}}> : tensor<4xi32> // CHECK-DAG: %[[EXPAND_DIM1:.+]] = arith.constant dense<3> : tensor<1xi32> // CHECK-DAG: %[[EXPAND_DIM0:.+]] = arith.constant dense<2> : tensor<1xi32> // CHECK: %[[EXPAND0:.+]] = "tfl.expand_dims"(%[[ARG0]], %[[EXPAND_DIM0]]) : (tensor<1x2x!quant.uniform<i8:f32, 2.000000e+00:3>>, tensor<1xi32>) -> tensor<1x2x1x!quant.uniform<i8:f32, 2.000000e+00:3>>
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/side-effect-analysis-test.mlir
// expected-remark@above {{Sinks: {}}} } // ----- func.func @add(%arg0: tensor<1xf32>, %arg1: tensor<1xf32>) -> tensor<1xf32> { // expected-remark@above {{ID: 2}} %sum = "tf.Add"(%arg0, %arg1) : (tensor<1xf32>, tensor<1xf32>) -> tensor<1xf32> // expected-remark@above {{ID: 0}} func.return %sum : tensor<1xf32> // expected-remark@above {{ID: 1}} // expected-remark@above {{Sinks: {}}} }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Dec 20 04:39:18 UTC 2023 - 129.7K bytes - Viewed (0) -
src/hash/crc32/crc32_table_ppc64le.s
DATA ·IEEEConst+1544(SB)/8,$0x0000000090db8c44 /* x^161856 mod p(x), x^161792 mod p(x) */ DATA ·IEEEConst+1552(SB)/8,$0x0000000067a2c786 DATA ·IEEEConst+1560(SB)/8,$0x000000010010a4ce /* x^160832 mod p(x), x^160768 mod p(x) */ DATA ·IEEEConst+1568(SB)/8,$0x0000000048b9496c DATA ·IEEEConst+1576(SB)/8,$0x00000001c8f4c72c /* x^159808 mod p(x), x^159744 mod p(x) */ DATA ·IEEEConst+1584(SB)/8,$0x000000015a422de6
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Mon Feb 19 20:44:20 UTC 2024 - 113.3K bytes - Viewed (0)