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Results 1 - 7 of 7 for 10x10xi32 (0.41 sec)
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tensorflow/compiler/mlir/lite/tests/prepare-tf.mlir
%1 = "tf.MatMul"(%arg0, %arg0) {device = "", transpose_a = false, transpose_b = false} : (tensor<10x10xi32>, tensor<10x10xi32>) -> tensor<10x10xi32> %2 = "tf.PreventGradient"(%0) : (tensor<10x10xi32>) -> tensor<10x10xi32> %3 = "tf.PreventGradient"(%1) : (tensor<10x10xi32>) -> tensor<10x10xi32> %4 = "tf.AddV2"(%2, %3) {device = ""} : (tensor<10x10xi32>, tensor<10x10xi32>) -> tensor<10x10xi32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 29 07:26:59 UTC 2024 - 59.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/optimize.mlir
%0 = arith.constant dense<-1> : tensor<1xi32> %1 = "tfl.reduce_max"(%arg0, %0) {keep_dims = true} : (tensor<10x10xf32>, tensor<1xi32>) -> tensor<10x1xf32> %2 = tfl.sub(%arg0, %1) {fused_activation_function = "NONE"} : (tensor<10x10xf32>, tensor<10x1xf32>) -> tensor<10x10xf32> %3 = "tfl.exp"(%2) : (tensor<10x10xf32>) -> tensor<10x10xf32>
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/tests/legalize-tf.mlir
} func.func @matmul_batch(%arg0: tensor<10x15xf32>, %arg1: tensor<15x17xf32>) -> tensor<10x17xf32> { %0 = "tf.BatchMatMul"(%arg0, %arg1) {T = "tfdtype$DT_FLOAT", device = "/device:CPU:0", name = "MatMul", adj_x = false, adj_y = false} : (tensor<10x15xf32>, tensor<15x17xf32>) -> tensor<10x17xf32> func.return %0 : tensor<10x17xf32> // CHECK-LABEL: matmul_batch
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/stablehlo/tests/legalize_hlo.mlir
%0 = "mhlo.broadcast_in_dim"(%arg1) <{broadcast_dimensions = dense<[0, 1]> : tensor<2xi64>}> : (tensor<1x1xi32>) -> tensor<1x100xi32> %1 = "mhlo.select"(%arg0, %0, %arg2) : (tensor<i1>, tensor<1x100xi32>, tensor<1x100xi32>) -> tensor<1x100xi32> func.return %1 : tensor<1x100xi32> } // CHECK-LABEL: func @selectv2_broadcasted_condition(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 29 07:26:59 UTC 2024 - 340.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/ops.mlir
// expected-error @+1 {{'tfl.prelu' op result type '10x10' not broadcast compatible with broadcasted operands's shapes '10x10x10x10'}} %0 = "tfl.prelu"(%arg0, %arg1) : (tensor<10x10x10x10xf32>, tensor<10x10x10x10xf32>) -> tensor<10x10xf32> func.return %0 : tensor<10x10xf32> } // -----
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/shape_inference.cc
} } return new_arg_type; } // Combination of value producer and port of value produced (e.g., // <value result output>:<value in output tensor>, // so for tf.Const -> tensor<10x20xf32>, [0,2,18] would point to a unique output // scalar value). struct ValuePort { PointerUnion<Operation*, BlockArgument> producer; SmallVector<unsigned int, 2> port;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Jun 08 07:28:49 UTC 2024 - 134.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/ir/tf_generated_ops.td
mlir_module = '''python func @main(%arg0 : tensor<10xf32>, %arg1 : tensor<10xf32>) -> tensor<10x10xf32> { %add = "magic.op"(%arg0, %arg1) : (tensor<10xf32>, tensor<10xf32>) -> tensor<10x10xf32> return %ret : tensor<10x10xf32> } ''' @tf.function def foo(x, y): return mlir_passthrough_op([x, y], mlir_module, Toutputs=[tf.float32])
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 23:24:08 UTC 2024 - 793K bytes - Viewed (0)