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Results 11 - 20 of 202 for conv3d (0.22 sec)
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tensorflow/compiler/mlir/quantization/tensorflow/passes/quantized_function_library.mlir
equation = "", attr_map = "equation:0" } : (tensor<*xi32>, tensor<*xi32>) -> tensor<*xi32> func.return %4 : tensor<*xi32> } for main_op in ["Conv2D", "DepthwiseConv2D", "MatMul", "Conv3D", "BatchMatMul", "Einsum"] { parameters[ {"quantized_ops": ["${main_op}", "BiasAdd"], "act_func": "internal_requantize_no_activation_fn", "output_type": "i8"},
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Jan 08 01:16:10 UTC 2024 - 30.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/lift_quantizable_spots_as_functions_drq.mlir
func.func @lift_float_conv3d(%arg0: tensor<1x3x4x3x3xf32>) -> (tensor<1x3x2x3x2xf32>) { %cst = "tf.Const"() {device = "", value = dense<1.0> : tensor<2x3x3x3x2xf32>} : () -> tensor<2x3x3x3x2xf32> %0 = "tf.Conv3D"(%arg0, %cst) { data_format = "NDHWC", device = "", dilations = [1, 1, 1, 1, 1], padding = "SAME", strides = [1, 1, 2, 1, 1] } : (tensor<1x3x4x3x3xf32>, tensor<2x3x3x3x2xf32>) -> tensor<1x3x2x3x2xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 11.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/replace_cast_hacks_with_tf_xla_ops.cc
// Input: [N, H, W, C] for Conv2D or [N, D, H, W, C] for Conv3D. dnums.set_input_batch_dimension(0); dnums.set_input_feature_dimension(num_dims - 1); // Kernel: [K, K, I, O] for Conv2D or [K, K, K, I, O] for Conv3D. dnums.set_kernel_input_feature_dimension(num_dims - 2); dnums.set_kernel_output_feature_dimension(num_dims - 1); // Output: [N, H, W, C] for Conv2D or [N, D, H, W, C] for Conv3D.
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 47.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/replace_cast_hacks_with_tf_xla_ops.td
(IsInt8ElementType $filter), (IsConstTensor $filter), (IsInt32ElementType $conv), (HasStaticShapeConstraint $filter), (HasStaticShapeAtDimsConstraint<"3"> $input)], [], (addBenefit 10)>; // Convert Conv2D with hybrid inputs (f32 activation/int8 weight) to XlaConv def ConvertTFConv2DToXLAConvOpWeightOnly : Pat< (TF_Conv2DOp:$conv $input, (TF_MulOp (TF_CastOp (TF_IdentityOp $filter), $truncate1), $scale),
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sun Dec 10 05:52:02 UTC 2023 - 21.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/schema/schema_v3b.fbs
table Conv2DOptions { padding:Padding; stride_w:int; stride_h:int; fused_activation_function:ActivationFunctionType; dilation_w_factor:int = 1; dilation_h_factor:int = 1; } // Options for both Conv3D and Conv3DTranspose. table Conv3DOptions { padding:Padding; stride_d:int; stride_w:int; stride_h:int; fused_activation_function:ActivationFunctionType; dilation_d_factor:int = 1;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 28 14:28:27 UTC 2024 - 30K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/schema/schema.fbs
fused_activation_function:ActivationFunctionType; dilation_w_factor:int = 1; dilation_h_factor:int = 1; // Parameters for Conv2D version 8 or above. // When set, quantized_bias_type defines the dtype for both bias and accumulator. quantized_bias_type: TensorType; } // Options for both Conv3D and Conv3DTranspose. table Conv3DOptions { padding:Padding; stride_d:int; stride_w:int; stride_h:int;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 03 18:01:23 UTC 2024 - 41.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/replace_cast_hacks_with_tf_xla_ops.mlir
%9 = "tf.Cast"(%6) {Truncate = false, device = ""} : (tensor<1x3x4x3x3xi32>) -> tensor<1x3x4x3x3xf32> %10 = "tf.Cast"(%8) {Truncate = false, device = ""} : (tensor<2x3x3x3x2xi32>) -> tensor<2x3x3x3x2xf32> %11 = "tf.Conv3D"(%9, %10) {device = "", dilations = [1, 1, 1, 1, 1], padding = "SAME", strides = [1, 1, 2, 1, 1]} : (tensor<1x3x4x3x3xf32>, tensor<2x3x3x3x2xf32>) -> tensor<1x3x2x3x2xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 81K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/python/integration_test/quantize_model_test.py
] ) def conv3d(self, input_tensor: core.Tensor) -> Mapping[str, core.Tensor]: """Performs a 3D convolution operation. Args: input_tensor: Input tensor to perform convolution on. Returns: A map of: output key -> output result. """ out = nn_ops.conv3d( input_tensor, self.filters,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 17 03:36:50 UTC 2024 - 235.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/legalize-tf.mlir
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/tensorflow/tests/tf-ops.mlir
%0 = "tf.Conv2D"(%arg0, %arg1) {padding = "SAME", strides = [1, 1, 1, 1]} : (tensor<*xf32>, tensor<*xf32>) -> tensor<?x?x?x?xf32> func.return %0 : tensor<?x?x?x?xf32> } // ----- // CHECK-LABEL: func @testValidConv3D func.func @testValidConv3D(%arg0: tensor<256x32x32x32x3xf32>, %arg1: tensor<3x3x3x3x16xf32>) -> tensor<256x32x32x32x16xf32> {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 23 14:40:35 UTC 2023 - 236.4K bytes - Viewed (0)