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Results 171 - 173 of 173 for conv_3d (0.15 sec)
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tensorflow/compiler/mlir/tf2xla/transforms/legalize_tf.cc
if (add.getType() != op.getType()) { add = rewriter.create<tensor::CastOp>(loc, op.getType(), add); } rewriter.replaceOp(op, {add}); return success(); } }; // Conterts tf.Conv2D to mhlo.dynamic_conv. // TODO(disc): To recover static special case's performance with adding folding, // canonicalization func and removing ConvertConvOp. template <typename OpT, int num_spatial_dims, bool depthwise_conv = false>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 20:00:43 UTC 2024 - 291.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/ir/tfl_ops.cc
return emitOptionalError(location, "invalid padding format provided"); } // Output always have rank 4. All dimensions are initialized to // dynamic size and can be partially inferred. // TFL's conv2d is always NHWC format & the filter is OHWI. SmallVector<int64_t, 4> return_shape(4, ShapedType::kDynamic); return_shape[0] = input_ty.getDimSize(0); return_shape[3] = filter_ty.getDimSize(0);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 169.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/ir/tf_generated_ops.td
w.r.t. the input of the convolution.}]>:$output ); TF_DerivedOperandTypeAttr T = TF_DerivedOperandTypeAttr<0>; } def TF_Conv3DOp : TF_Op<"Conv3D", [InferTensorType, Pure]> { let summary = [{ Computes a 3-D convolution given 5-D `input` and `filter` tensors. }]; let description = [{
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 23:24:08 UTC 2024 - 793K bytes - Viewed (0)