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tensorflow/compiler/mlir/tfrt/runtime_fallback/runtime_fallback_ops.td
TFRT attributes are sorted alphabetically, passed in as positional attributes to the TFRT kernel, rather than as named attributes. Example: To run "tf.MatMul" op, which has two boolean attributes, 1. Set _name = "MatMul" 2. For each TF attribute, split it into two attributes, one for name of the TF attribute, and the other for the type and value of the
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Feb 23 19:35:12 UTC 2023 - 5.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/fused_kernel_matcher.mlir
%3 = "tf.Identity"(%2) : (tensor<*xf32>) -> tensor<*xf32> func.return %3 : tensor<*xf32> } //===----------------------------------------------------------------------===// // MatMul + BiasAdd + <Activation> fusions. //===----------------------------------------------------------------------===// // CHECK-LABEL: matmulBiasAdd
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 13.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/python/integration_test/quantize_model_test.py
).astype(np.float32) class TwoMatmulModel(module.Module): """A model with two matmul ops.""" @def_function.function def matmul(self, input_tensor: core.Tensor) -> Mapping[str, core.Tensor]: """Performs a matrix multiplication. Args: input_tensor: Input tensor to matmul with the filter. Returns: A 'output' -> output tensor mapping """
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 14 06:31:57 UTC 2024 - 51.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/tests/tf_to_corert/device_conversion.mlir
%arg1: tensor<1x3xf32> {tf_saved_model.index_path = [0]}) -> (tensor<3x3xf32> {tf_saved_model.index_path = []}) { // CHECK: {{%.*}} = corert.get_op_handler %arg0 "/device:GPU:0" %2 = "tf.MatMul"(%arg0, %arg1) {T = f32, _output_shapes = ["tfshape$dim { size: 3 } dim { size: 3 }"], device = "/device:GPU:0", transpose_a = false, transpose_b = false} : (tensor<3x1xf32>, tensor<1x3xf32>) -> tensor<3x3xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 08 00:18:59 UTC 2024 - 645 bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/python/integration_test/quantize_model_test_base.py
@def_function.function def matmul(self, input_tensor: core.Tensor) -> Mapping[str, core.Tensor]: """Performs a matrix multiplication. Depending on self.has_bias and self.activation_fn, it may add a bias term or go through the activaction function. Args: input_tensor: Input tensor to matmul with the filter. Returns:
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Mar 21 08:51:46 UTC 2024 - 51.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/tests/tf_to_corert/attributes.mlir
// CHECK: {{%.*}} = tfrt_fallback_async.executeop {{.*}} device("/device:CPU:0") "tf.MatMul" // CHECK-SAME: {T = f32, transpose_a = false, transpose_b = false}
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 08 00:18:59 UTC 2024 - 4.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/tests/tf_to_corert/basic.mlir
// CHECK-NEXT: [[ch1:%.*]], [[var:%.*]] = tfrt_fallback_async.executeop.seq([[in_chain]]) {{.*}} "tf.ReadVariableOp"([[arg1]]) // CHECK-NEXT: [[r0:%.*]] = tfrt_fallback_async.executeop {{.*}} "tf.MatMul"([[arg0]], [[var]]) %2 = "tf.MatMul"(%arg0, %1) {T = f32, _output_shapes = ["tfshape$dim { size: 3 } dim { size: 3 }"], device = "/device:CPU:0", transpose_a = false, transpose_b = false} : (tensor<3x1xf32>, tensor<1x3xf32>) -> tensor<3x3xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 08 00:18:59 UTC 2024 - 3.9K bytes - Viewed (0) -
tensorflow/compiler/jit/tests/keras_imagenet_main_graph_mode.golden_summary
BiasAdd 1 BiasAddGrad 1 Cast 3 Const 357 Conv2D 53 Conv2DBackpropFilter 53 Conv2DBackpropInput 52 DivNoNan 1 Equal 1 FusedBatchNorm 53 FusedBatchNormGrad 53 Identity 2 MatMul 3 MaxPool 1 MaxPoolGrad 1 Mean 1 Mul 164 Pad 1 ReadVariableOp 646 Relu 49 ReluGrad 49 Reshape 2 ResourceApplyKerasMomentum 161 ShapeN 50 Softmax 1
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Jan 06 10:38:14 UTC 2023 - 740 bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/insert_quantized_functions_drq.mlir
// CHECK-NOT: func private @internal_quantize_i8 // CHECK-NOT: func private @internal_matmul_fn // CHECK: func private @quantized_matmul_fn // CHECK-SAME: tf_quant.quantized_ops = ["MatMul"] // CHECK: func private @quantized_conv2d_fn // CHECK-SAME: tf_quant.quantized_ops = ["Conv2D"] // CHECK: func private @quantized_depthwise_conv2d_fn // CHECK-SAME: tf_quant.quantized_ops = ["DepthwiseConv2D"]
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Dec 01 12:06:54 UTC 2022 - 1K bytes - Viewed (0) -
tensorflow/compiler/jit/tests/keras_imagenet_main.golden_summary
ArgMax 1 AssignAddVariableOp 1 BiasAdd 1 BiasAddGrad 1 Cast 115 Const 407 Conv2D 53 Conv2DBackpropFilter 53 Conv2DBackpropInput 52 Equal 1 FusedBatchNormGradV2 53 FusedBatchNormV2 53 MatMul 3 MaxPool 1 MaxPoolGrad 1 Mean 1 Mul 218 Pad 2 ReadVariableOp 538 Relu 49 ReluGrad 49 Reshape 2 ResourceApplyKerasMomentum 161 Slice 1 Softmax 1
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Jan 06 10:38:14 UTC 2023 - 874 bytes - Viewed (0)