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Results 21 - 30 of 31 for 8x1xf32 (0.21 sec)
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tensorflow/compiler/mlir/lite/tests/prepare-quantize-signed.mlir
} // CHECK-LABEL: prepareAdd func.func @prepareAdd(%arg0: tensor<2x2xf32>) -> tensor<2x2xf32> { %cst = arith.constant dense<[[0.0, 1.0], [2.0, 255.0]]> : tensor<2x2xf32> %add = "tfl.add"(%arg0, %cst) {fused_activation_function="NONE"} : (tensor<2x2xf32>, tensor<2x2xf32>) -> tensor<2x2xf32> func.return %add : tensor<2x2xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 18.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/canonicalize.mlir
func.func @RemoveRedundantUnpackPack(%arg0: tensor<2x5xf32>) -> tensor<2x5xf32> { %0:2 = "tfl.unpack"(%arg0) {axis = 0 : i32, num = 2 : i32} : (tensor<2x5xf32>) -> (tensor<5xf32>, tensor<5xf32>) %1 = "tfl.pack"(%0#0, %0#1) {axis = 0 : i32, values_count = 2 : i32} : (tensor<5xf32>, tensor<5xf32>) -> (tensor<2x5xf32>) func.return %1: tensor<2x5xf32> // CHECK-NOT: pack // CHECK: return %arg0 : tensor<2x5xf32> } // -----
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 20.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/insert_weight_param.mlir
version = 5 : i64 } : (tensor<1x2xf32>, tensor<2x3xf32>) -> tensor<1x3xf32> return %0 : tensor<1x3xf32> } // CHECK-LABEL: func.func @qdq_for_dot_general_weight_empty // CHECK-SAME: (%[[ARG_0:.+]]: tensor<1x2xf32>) -> tensor<1x3xf32> // CHECK: %[[CST:.+]] = "tf.Const"() <{value = dense<3.000000e-01> : tensor<2x3xf32>}> : () -> tensor<2x3xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 09 05:56:10 UTC 2024 - 22K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/quantize.mlir
} // CHECK-LABEL: QuantizeConcat func.func @QuantizeConcat(tensor<1x2xf32>, tensor<1x2xf32>) -> tensor<2x2x!quant.uniform<u8:f32, 1.000000e-01:128>> { ^bb0(%arg0: tensor<1x2xf32>, %arg1: tensor<1x2xf32>): %0 = "tfl.concatenation"(%arg0, %arg1) {axis = 0 : i32, fused_activation_function = "NONE"} : (tensor<1x2xf32>, tensor<1x2xf32>) -> tensor<2x2xf32>
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/tensorflow/tests/tpu_sharding_identification.mlir
} func.func @_func(%arg0: tensor<2x4xf32>, %arg1: tensor<4x2xf32>) -> tensor<2x2xf32> { %0 = "tf.MatMul"(%arg0, %arg1) {_XlaSharding = "\08\03\1A\02\02\01\22\02\00\01"} : (tensor<2x4xf32>, tensor<4x2xf32>) -> tensor<2x2xf32> %1 = "tf.Identity"(%0) : (tensor<2x2xf32>) -> tensor<2x2xf32> return %1 : tensor<2x2xf32> } // ----- // The following op sharding is used in the following test case:
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Feb 20 19:07:52 UTC 2024 - 47.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/tfl_while_outline.mlir
%9 = "tfl.fully_connected"(%8, %cst_10, %cst_0) {fused_activation_function = "NONE", keep_num_dims = false, weights_format = "DEFAULT"} : (tensor<4x5xf32>, tensor<8x5xf32>, tensor<8xf32>) -> tensor<4x8xf32> %10:4 = "tfl.split"(%cst_5, %9) {num_splits = 4 : i32} : (tensor<i32>, tensor<4x8xf32>) -> (tensor<4x2xf32>, tensor<4x2xf32>, tensor<4x2xf32>, tensor<4x2xf32>)
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 13.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/tfl_legalize_hlo.mlir
func.func @main(%arg0: tensor<5x7xf32>) -> tensor<5x7xf32> { func.return %arg0: tensor<5x7xf32> // CHECK-LABEL: main // CHECK: return %arg0 : tensor<5x7xf32> } // - transpose // func.func @transpose_2d(%arg0: tensor<2x3xf32>) -> tensor<3x2xf32> { %0 = "mhlo.transpose"(%arg0) <{permutation = dense<[1, 0]> : tensor<2xi64>}> : (tensor<2x3xf32>) -> tensor<3x2xf32> func.return %0 : tensor<3x2xf32>
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/const-fold.mlir
func.func @add_dense_dense_float_mixfng_1_n() -> tensor<2x2xf32> { %cst_0 = arith.constant dense<[[1.5, -2.5]]> : tensor<1x2xf32> %cst_1 = arith.constant dense<[[-3.], [4.]]> : tensor<2x1xf32> %0 = "tfl.add"(%cst_0, %cst_1) {fused_activation_function = "NONE"} : (tensor<1x2xf32>, tensor<2x1xf32>) -> tensor<2x2xf32> func.return %0 : tensor<2x2xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 45.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/tests/mlrt/tf_to_mlrt.mlir
// Test for XlaLaunch func.func private @xla_func_0(%arg0: tensor<1x3xf32>, %arg1: tensor<1x3xf32>) -> tensor<1x3xf32> attributes {tf._XlaMustCompile = true, tf._noinline = true, tf._original_func_name = "should_not_be_used"} { %1 = "tf.AddV2"(%arg0, %arg1) {__op_key = 0: i32} : (tensor<1x3xf32>, tensor<1x3xf32>) -> tensor<1x3xf32> func.return %1 : tensor<1x3xf32> } // CHECK-LABEL: func @xla_func
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 31 20:44:15 UTC 2024 - 24.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/composite-lowering.mlir
func.func private @gelu_decomp_2(%arg0: tensor<5x10xf32>) -> tensor<5x10xf32> func.func @gelu_aten_approximate(%arg0: tensor<5x10xf32>) -> (tensor<*xf32>) { %0 = mhlo.composite "aten.gelu.default" %arg0 {composite_attributes = {approximate = "tanh"}, decomposition = @gelu_decomp_2} : (tensor<5x10xf32>) -> tensor<5x10xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jun 06 18:45:51 UTC 2024 - 32.6K bytes - Viewed (0)