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Results 1 - 10 of 31 for 1x1x5xf32 (0.17 sec)
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tensorflow/compiler/mlir/lite/tests/prepare-quantize-post-training.mlir
} // CHECK-LABEL: QuantizeWithoutNorm func.func @QuantizeWithoutNorm(%arg0: tensor<1x1x5xf32>) -> tensor<*xf32> attributes {tf.entry_function = {inputs = "input0", outputs = "output24"}} { %none = "tfl.no_value"() {value = unit} : () -> none %input = "quantfork.stats"(%arg0) {layerStats = dense<[-1.2, 1.5]> : tensor<2xf32>} : (tensor<1x1x5xf32>) -> tensor<1x1x5xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 52.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/compose-uniform-quantized-type.mlir
%14 = stablehlo.multiply %12, %13 : tensor<1x4x3xf32> // s1 * s2 %15 = call @uniform_quantize_1(%14, %5, %6) : (tensor<1x4x3xf32>, tensor<1x1x1xf32>, tensor<1x1x1xi8>) -> tensor<1x4x3xi8> %16 = call @uniform_dequantize_0(%15, %5, %6) : (tensor<1x4x3xi8>, tensor<1x1x1xf32>, tensor<1x1x1xi8>) -> tensor<1x4x3xf32> return %16 : tensor<1x4x3xf32> }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 14 17:10:32 UTC 2024 - 37K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/unroll-batch-matmul.mlir
// CHECK: %[[LHS_SPLIT:.*]]:6 = "tf.Split"(%[[SPLITTING_AXIS]], %[[LHS_RESHAPED]]) : (tensor<i32>, tensor<6x4x5xf32>) -> (tensor<1x4x5xf32>, tensor<1x4x5xf32>, tensor<1x4x5xf32>, tensor<1x4x5xf32>, tensor<1x4x5xf32>, tensor<1x4x5xf32>) // CHECK: %[[LHS_1:.*]] = "tf.Reshape"(%[[LHS_SPLIT]]#0, %[[MATMUL_LHS_SHAPE]]) : (tensor<1x4x5xf32>, tensor<2xi64>) -> tensor<4x5xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Dec 06 18:42:28 UTC 2023 - 63.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/ops/stablehlo_op_quant_spec_test.cc
return %0 : tensor<1x1x4xf32> } )mlir"; OwningOpRef<ModuleOp> module_op = ParseModuleOpString(kModuleXlaCallModuleOpWithDefaultQuantizationMethod); ASSERT_TRUE(module_op);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 04 07:19:09 UTC 2024 - 14.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/prepare-quantize-post-training-16bits.mlir
time_major = false} : ( tensor<1x2x3xf32>, tensor<1x1xf32>, tensor<1x1xf32>, tensor<1x1xf32>, tensor<1x1xf32>, tensor<1x1xf32>, tensor<1x1xf32>, tensor<1x1xf32>, tensor<1x1xf32>, none, none, none, tensor<3xf32>, tensor<3xf32>, tensor<3xf32>, tensor<3xf32>, none, none, tensor<1x3xf32>, tensor<1x3xf32>, none, none, none, none) -> tensor<1x2x3xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 26.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/lift_as_function_call_test.cc
return %0 : tensor<1x1x4xf32> } )mlir"; const OwningOpRef<ModuleOp> module_op = ParseModuleOpString(kXlaCallModuleOpWithQuantizationMethodAttr); ASSERT_TRUE(module_op);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 10 04:07:09 UTC 2024 - 26.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/optimize.mlir
func.func @testRemoveReshapeAroundDot(%arg0: tensor<1x1x512xf32>, %arg1: tensor<512x13x!quant.uniform<i8:f32, 0.00285>>) -> tensor<1x1x13xf32> { %0 = "mhlo.reshape"(%arg0) : (tensor<1x1x512xf32>) -> tensor<1x512xf32> %1 = "mhlo.dot"(%0, %arg1) : (tensor<1x512xf32>, tensor<512x13x!quant.uniform<i8:f32, 0.00285>>) -> tensor<1x13xf32> %2 = "mhlo.reshape"(%1) : (tensor<1x13xf32>) -> tensor<1x1x13xf32> func.return %2 : tensor<1x1x13xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Apr 06 15:32:52 UTC 2024 - 22.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/cast_bf16_ops_to_f32.mlir
%2 = "tf.Cast"(%1) {Truncate = false} : (tensor<1x1x2xbf16>) -> tensor<1x1x2xf32> %3 = "tf.IdentityN"(%2) {device = ""} : (tensor<1x1x2xf32>) -> tensor<1x1x2xf32> return %3 : tensor<1x1x2xf32> } // CHECK: func @cast_bf16_batch_matmul_v2_to_fp32 // CHECK-DAG: %[[cst:.*]] = "tf.Const"() <{value = dense<{{.*}}> : tensor<10x2xf32>}> : () -> tensor<10x2xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 8.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/optimize.mlir
%3 = "tfl.div"(%2, %arg1) {fused_activation_function = "NONE"} : (tensor<1x128xf32>, tensor<1x128xf32>) -> tensor<1x128xf32> func.return %3 : tensor<1x128xf32> // CHECK-DAG: %[[cst:.*]] = arith.constant dense<1.000000e+00> : tensor<f32> // CHECK: %[[ADD:[0-9].*]] = tfl.add(%arg0, %[[cst]]) <{fused_activation_function = "NONE"}> : (tensor<1x1xf32>, tensor<f32>) -> tensor<1x1xf32>
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/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)