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Results 41 - 50 of 134 for 186xf32 (0.1 sec)
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tensorflow/compiler/mlir/quantization/common/attrs_and_constraints_test.cc
%cst = stablehlo.constant dense<1.0> : tensor<1x3xf32> %0 = stablehlo.dot_general %arg0, %arg1, contracting_dims = [1] x [0], precision = [] : (tensor<1x1024xf32>, tensor<1024x3xf32>) -> tensor<1x3xf32> %1 = stablehlo.subtract %cst, %0 : tensor<1x3xf32> %2 = stablehlo.add %0, %cst : tensor<1x3xf32> return %2 : tensor<1x3xf32> } }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 14 17:10:32 UTC 2024 - 22.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/constant-fold.mlir
} // CHECK-LABEL: func @testLeakyRelu func.func @testLeakyRelu(%arg0 : tensor<16xf32>) -> (tensor<16xf32>, tensor<f32>, tensor<f32>, tensor<16xf32>) { %pos = arith.constant dense<5.0> : tensor<f32> %neg = arith.constant dense<-5.0> : tensor<f32> %no = "tf.LeakyRelu"(%arg0) {alpha = 0.2 : f32} : (tensor<16xf32>) -> tensor<16xf32> %0 = "tf.LeakyRelu"(%pos) {alpha = 0.3 : f32} : (tensor<f32>) -> tensor<f32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jan 31 23:22:24 UTC 2024 - 36.7K 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/sink_constant.mlir
%3 = "tf.Mul"(%arg0, %0) : (tensor<16xf32>, tensor<f32>) -> tensor<16xf32> %4 = "tf.Mul"(%3, %0) : (tensor<16xf32>, tensor<f32>) -> tensor<16xf32> %5 = "tf.Mul"(%4, %1) : (tensor<16xf32>, tensor<f32>) -> tensor<16xf32> %6 = "tf.Mul"(%5, %2) : (tensor<16xf32>, tensor<f32>) -> tensor<16xf32> tf_device.return %6 : tensor<16xf32> }) {} : () -> tensor<16xf32> tf_executor.yield %3 : tensor<16xf32> }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Mar 24 05:47:26 UTC 2022 - 1.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/optimize.mlir
%2 = "tf.Mul"(%1, %value) {T = "tfdtype$DT_FLOAT"} : (tensor<256x8x7x16xf32>, tensor<16xf32>) -> tensor<256x8x7x16xf32> func.return %2 : tensor<256x8x7x16xf32> // CHECK-DAG: %[[cst:.*]] = "tf.Const{{.*}} dense<8.000000e+00> : tensor<3x3x3x16xf32> // CHECK-DAG: %[[cst_0:.*]] = "tf.Const{{.*}} dense<1.200000e+01> : tensor<16xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Jan 05 18:35:42 UTC 2024 - 3.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/mlir2graphdef/type_attr.mlir
// CHECK: Placeholder // CHECK: key: "type" // CHECK: type: DT_INT8 func.func @main(%arg0 : tensor<16xf32>) { tf_executor.graph { %1:2 = tf_executor.island wraps "tf.MlirPassthroughOp"(%arg0) {extra_type_attr = [tensor<5xi32>, tensor<16xf32>], Tinputs = [tensor<16xf32>], Toutputs = [tensor<16xf32>], mlir_module = ""} : (tensor<16xf32>) -> tensor<16xf32> tf_executor.fetch } func.return } func.func @plain() { tf_executor.graph {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Mar 28 12:06:33 UTC 2022 - 1.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/canonicalize.mlir
func.func @addNSkipFoldingIfBroadcasting(%arg0: tensor<1xf32>) -> tensor<10xf32> { %0 = "tf.Const"() {value = dense<0.000000e+00> : tensor<10xf32>} : () -> tensor<10xf32> // CHECK: [[ZERO:%.*]] = "tf.Const"() <{value = dense<0.000000e+00> : tensor<10xf32>}> // CHECK: [[ADD_N:%.*]] = "tf.AddN"(%arg0, [[ZERO]]) // CHECK: return [[ADD_N]] %1 = "tf.AddN"(%arg0, %0) : (tensor<1xf32>, tensor<10xf32>) -> tensor<10xf32> func.return %1: tensor<10xf32> }
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/quantization/tensorflow/tests/tf_to_quant.mlir
%min = arith.constant dense<0.0> : tensor<16xf32> %max = arith.constant dense<255.0> : tensor<16xf32> %mini = "tf.Identity"(%min) : (tensor<16xf32>) -> tensor<16xf32> %maxi = "tf.Identity"(%max) : (tensor<16xf32>) -> tensor<16xf32> %fq = "tf.FakeQuantWithMinMaxVarsPerChannel"(%in, %mini, %maxi) {num_bits = 5, narrow_range = false} : (tensor<3x3x3x16xf32>, tensor<16xf32>, tensor<16xf32>) -> tensor<3x3x3x16xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 9.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/tensorflow/tests/tf_to_quant_4bit.mlir
%min = arith.constant dense<0.0> : tensor<16xf32> %max = arith.constant dense<15.0> : tensor<16xf32> %mini = "tf.Identity"(%min) : (tensor<16xf32>) -> tensor<16xf32> %maxi = "tf.Identity"(%max) : (tensor<16xf32>) -> tensor<16xf32> %fq = "tf.FakeQuantWithMinMaxVarsPerChannel"(%in, %mini, %maxi) {num_bits = 3, narrow_range = false} : (tensor<3x3x3x16xf32>, tensor<16xf32>, tensor<16xf32>) -> tensor<3x3x3x16xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 9.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/tac/tests/fold-constants-to-subgraph.mlir
%2 = func.call @fold_all_test(%arg0, %0, %1) : (tensor<256x32x32x3xf32>, tensor<16x3x3x3xf32>, tensor<16xf32>) -> tensor<256x30x30x16xf32> func.return %2 : tensor<256x30x30x16xf32> } // ALL-LABEL: @fold_all_test func.func @fold_all_test(%arg0: tensor<256x32x32x3xf32>, %arg1: tensor<16x3x3x3xf32>, %arg2: tensor<16xf32>) -> tensor<256x30x30x16xf32> {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 10.5K bytes - Viewed (0)