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Results 1 - 10 of 19 for 28x1x8xf32 (0.16 sec)
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tensorflow/compiler/mlir/lite/tests/legalize-tf.mlir
// CHECK: return } func.func @pow(%arg0: tensor<2x1x3xf32>, %arg1: tensor<2x1x1xf32>) -> tensor<2x1x3xf32> { %0 = "tf.Pow"(%arg0, %arg1) : (tensor<2x1x3xf32>, tensor<2x1x1xf32>) -> tensor<2x1x3xf32> func.return %0 : tensor<2x1x3xf32> // CHECK-LABEL: pow // CHECK: %[[pow:.*]] = tfl.pow(%arg0, %arg1) : (tensor<2x1x3xf32>, tensor<2x1x1xf32>) -> tensor<2x1x3xf32> // CHECK: return }
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/einsum.mlir
// CHECK: return %[[v5]] : tensor<?x?x8xf32> } func.func @einsum_no_reshape(%arg0 : tensor<?x?x8x128xf32>, %arg1 : tensor<1x?x8x128xf32>) -> tensor<?x?x8x?xf32> { %0 = "tf.Einsum"(%arg0, %arg1) {device = "", equation = "BQNH,BTNH->BQNT"} : (tensor<?x?x8x128xf32>, tensor<1x?x8x128xf32>) -> tensor<?x?x8x?xf32> func.return %0 : tensor<?x?x8x?xf32> // CHECK-LABEL: einsum_no_reshape
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Jan 05 18:35:42 UTC 2024 - 25.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/legalize-tfl-stablehlo-pad.mlir
module { func.func @main(%arg0: tensor<8x128xf32>, %arg1: tensor<f32>) -> tensor<11x131xf32> { %0 = "tfl.custom"(%arg0, %arg1) {custom_code = "stablehlo.pad", custom_option = #tfl<const_bytes : "0x656467655F70616464696E675F6869676800020203656467655F70616464696E675F6C6F7700020100696E746572696F725F70616464696E6700020000033E2A17030103311E0B2C2C2C062401">} : (tensor<8x128xf32>, tensor<f32>) -> tensor<11x131xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Dec 11 20:41:19 UTC 2023 - 939 bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/tf-tfl-translate-tf-quantize.mlir
module { func.func @tfInplaceUpdate(%arg0: tensor<2x1x2xf32>) -> tensor<2x1x2xf32> { %1 = arith.constant dense<1> : tensor<1xi32> %2 = arith.constant dense<2.0> : tensor<1x1x2xf32> %3 = "tf.InplaceUpdate"(%arg0, %1, %2) {device = ""} : (tensor<2x1x2xf32>, tensor<1xi32>, tensor<1x1x2xf32>) -> tensor<2x1x2xf32> func.return %3 : tensor<2x1x2xf32> } } //CHECK: module {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sun Apr 14 18:33:43 UTC 2024 - 1.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/default_quant_params.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 8.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/tf-tfl-translate-serialize-stablehlo.mlir
module { func.func @tfInplaceUpdate(%arg0: tensor<2x1x2xf32>) -> tensor<2x1x2xf32> { %1 = arith.constant dense<1> : tensor<1xi32> %2 = arith.constant dense<2.0> : tensor<1x1x2xf32> %3 = "tf.InplaceUpdate"(%arg0, %1, %2) {device = ""} : (tensor<2x1x2xf32>, tensor<1xi32>, tensor<1x1x2xf32>) -> tensor<2x1x2xf32> func.return %3 : tensor<2x1x2xf32> } } //CHECK: module attributes
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sun Apr 14 18:33:43 UTC 2024 - 1.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/quantize.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 28 23:10:13 UTC 2024 - 39.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/quantize-numeric-verify.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 15.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/tac/tests/raise-target-subgraphs.mlir
%4 = "tfl.relu"(%3) {tac.device = "GPU", tac.inference_type = "FLOAT"} : (tensor<128x128xf32>) -> tensor<128x128xf32> %5 = "tfl.pseudo_const"() {value = dense<1.000000e+00> : tensor<128x128xf32>} : () -> tensor<128x128xf32> %6 = "tfl.pseudo_const"() {value = dense<1.000000e+00> : tensor<128xf32>} : () -> tensor<128xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 74.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/optimize.mlir
%cst = arith.constant dense<1> : tensor<1xi32> %0 = "tfl.exp"(%arg0) : (tensor<8x128xf32>) -> tensor<8x128xf32> %1 = "tfl.sum"(%0, %cst) {keep_dims = true} : (tensor<8x128xf32>, tensor<1xi32>) -> tensor<8x1xf32> %2 = "tfl.div"(%0, %1) {fused_activation_function = "NONE"} : (tensor<8x128xf32>, tensor<8x1xf32>) -> tensor<8x128xf32> func.return %2 : tensor<8x128xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 16 20:31:41 UTC 2024 - 284.1K bytes - Viewed (0)