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Results 1 - 10 of 16 for 8x16x4xf32 (0.27 sec)
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tensorflow/compiler/mlir/lite/stablehlo/tests/compose-uniform-quantized-type.mlir
%19 = stablehlo.convert %18 : (tensor<8x16x4xi32>) -> tensor<8x16x4xf32> %20 = stablehlo.broadcast_in_dim %9, dims = [0, 1, 2] : (tensor<1x1x1xf32>) -> tensor<8x16x4xf32> %21 = stablehlo.multiply %19, %20 : tensor<8x16x4xf32> // * s1 s2 %22 = call @uniform_quantize_1(%21, %7, %8) : (tensor<8x16x4xf32>, tensor<1x1x1xf32>, tensor<1x1x1xi8>) -> tensor<8x16x4xi8>
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/lite/tests/legalize-tf.mlir
func.return %0 : tensor<8x16xf32> // CHECK-LABEL:minimum // CHECK: "tfl.minimum"(%arg0, %arg1) : (tensor<8x16xf32>, tensor<8x16xf32>) -> tensor<8x16xf32> } func.func @realDiv(%arg0: tensor<8x16xf32>, %arg1: tensor<8x16xf32>) -> tensor<8x16xf32> { %0 = "tf.RealDiv"(%arg0, %arg1) : (tensor<8x16xf32>, tensor<8x16xf32>) -> tensor<8x16xf32>
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/tests/prepare-composite-functions-tf.mlir
%44 = "tf.AddV2"(%43, %37) {device = ""} : (tensor<2x16x1xf32>, tensor<2x16x1xf32>) -> tensor<2x16x1xf32> %45 = "tf.Mul"(%42, %35) {device = ""} : (tensor<2x16x1xf32>, tensor<2x16x1xf32>) -> tensor<2x16x1xf32> %46 = "tf.AddV2"(%45, %34) {device = ""} : (tensor<2x16x1xf32>, tensor<2x16x1xf32>) -> tensor<2x16x1xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 122.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/lift_quantizable_spots_as_functions.mlir
%5 = stablehlo.broadcast_in_dim %1, dims = [2] : (tensor<64xf32>) -> tensor<1x1x64xf32> %6 = stablehlo.add %4, %5 : tensor<1x1x64xf32> %7 = stablehlo.clamp %2, %6, %3 : tensor<1x1x64xf32> func.return %7: tensor<1x1x64xf32> } // CHECK: %[[CONST_0:.*]] = stablehlo.constant dense<2.000000e+00> // CHECK: %[[CONST_1:.*]] = stablehlo.constant dense<2.000000e+00>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 10 04:07:09 UTC 2024 - 49.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/tensorflow/tests/fallback_to_flex_ops_legacy.mlir
} // CHECK-LABEL: softmax func.func @softmax(%arg0: tensor<8x16xf32>) -> tensor<8x16xf32> { %0 = "tf.Softmax"(%arg0) : (tensor<8x16xf32>) -> tensor<8x16xf32> func.return %0 : tensor<8x16xf32> // CHECK: %[[SOFTMAX_0:.*]] = "tf.Softmax"(%arg0) : (tensor<8x16xf32>) -> tensor<8x16xf32> // CHECK: return %[[SOFTMAX_0]] : tensor<8x16xf32> } // CHECK-LABEL: conv2d_backprop_input_with_add
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 5.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/canonicalize.mlir
// CHECK: return %0 } // CHECK-LABEL: testAddOfNegRight func.func @testAddOfNegRight(%arg0: tensor<8x16xf32>, %arg1: tensor<8x16xf32>) -> tensor<8x16xf32> { %0 = "tf.Neg"(%arg1) : (tensor<8x16xf32>) -> tensor<8x16xf32> %1 = "tf.Add"(%arg0, %0) {device = "/job:localhost/replica:0/task:0/device:GPU:0"} : (tensor<8x16xf32>, tensor<8x16xf32>) -> tensor<8x16xf32>
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/quantization/common/lift_as_function_call_test.cc
return %0 : tensor<1x1x4xf32> } )mlir"; const OwningOpRef<ModuleOp> module_op = ParseModuleOpString(kXlaCallModuleOpWithQuantizationMethodAttr); ASSERT_TRUE(module_op); func::FuncOp main_fn = FindMainFuncOp(*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/tests/canonicalize.mlir
func.func @reshape_vector_shape(tensor<4x4x4xf32>) -> tensor<16x4xf32> { ^bb0(%arg0: tensor<4x4x4xf32>) : %shape0 = arith.constant dense<[[16, 4]]> : tensor<1x2xi32> // expected-error @+1 {{'tfl.reshape' op requires 'shape' to be rank 1, but got 2}} %1 = "tfl.reshape"(%arg0, %shape0) : (tensor<4x4x4xf32>, tensor<1x2xi32>) -> tensor<16x4xf32> func.return %1 : tensor<16x4xf32> } // -----
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/lite/quantization/tensorflow/tests/fallback_to_flex_ops_default.mlir
func.func @softmax(%arg0: tensor<8x16xf32>) -> tensor<8x16xf32> { %0 = "tf.Softmax"(%arg0) : (tensor<8x16xf32>) -> tensor<8x16xf32> func.return %0 : tensor<8x16xf32> // CHECK: %[[CUSTOM_0:.*]] = "tfl.custom"(%arg0) <{custom_code = "FlexSoftmax", custom_option = #tfl<const_bytes : "0x07536F66746D617800161207536F66746D61781A002A070A0154120230013200000221191414042801">}> : (tensor<8x16xf32>) -> tensor<8x16xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 13.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/optimize_batch_matmul.mlir
%1 = "tfl.fully_connected"(%0, %arg1, %cst_1) {asymmetric_quantize_inputs = false, fused_activation_function = "NONE", keep_num_dims = false, weights_format = "DEFAULT"} : (tensor<4x1024xf32>, tensor<8x1024xf32>, none) -> tensor<4x8xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 9K bytes - Viewed (0)