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Results 1 - 9 of 9 for diagonal (0.41 sec)
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tensorflow/compiler/mlir/lite/transforms/prepare_patterns.td
Pat<(TF_MatrixSetDiagV2Op $input, $diagonal, (Arith_ConstantOp ConstantAttr<I32ElementsAttr, "{0}">)), (TF_MatrixSetDiagOp $input, $diagonal)>; // `align` attribute can be ignored because we only support converting // `MatrixSetDiagV3` to `MatrixSetDiag` with default `k` inputs. def ConvertMatrixSetDiagV3ToMatrixSetDiag : Pat<(TF_MatrixSetDiagV3Op $input, $diagonal,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 30 00:40:15 UTC 2024 - 10.5K bytes - Viewed (0) -
src/image/gif/writer_test.go
var buf bytes.Buffer if err := Encode(&buf, src, nil); err != nil { t.Errorf("gray-diagonal: Encode: %v", err) return } m, err := Decode(&buf) if err != nil { t.Errorf("gray-diagonal: Decode: %v", err) return } if got, want := m.Bounds(), image.Rect(0, 0, 6, 6); got != want { t.Errorf("gray-diagonal: got %v, want %v", got, want) return }
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Mon Jun 03 14:56:25 UTC 2024 - 19K bytes - Viewed (0) -
src/vendor/golang.org/x/crypto/chacha20/chacha_generic.go
const blockSize = 64 // quarterRound is the core of ChaCha20. It shuffles the bits of 4 state words. // It's executed 4 times for each of the 20 ChaCha20 rounds, operating on all 16 // words each round, in columnar or diagonal groups of 4 at a time. func quarterRound(a, b, c, d uint32) (uint32, uint32, uint32, uint32) { a += b d ^= a d = bits.RotateLeft32(d, 16) c += d b ^= c b = bits.RotateLeft32(b, 12) a += b
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Wed Oct 26 00:11:50 UTC 2022 - 13.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/legalize_patterns.td
(TFL_NonMaxSuppressionV5Op $boxes, $scores, $max_output_size, $iou_threshold, $score_threshold, $soft_nms_sigma)>; def LegalizeMatrixDiag : Pat<(TF_MatrixDiagOp $diagonal), (TFL_MatrixDiagOp $diagonal)>; def LegalizeConv2DBackpropInput : Pat< (TF_Conv2DBackpropInputOp $input_sizes, $filter, $out_backprop, IsIntList1XY1:$strides, BoolAttr:$use_cudnn_on_gpu,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 04 13:30:42 UTC 2024 - 28.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/prepare_composite_functions_tf.cc
// LSTM `func::FuncOps` with indy behavior always have the `tf.api_implements` // function attribute prefixed with `"indy_lstm_"`. // IndyLSTMs have diagonal recurrent weight matrices and can benefit from // more efficent operations in TFLite with the correct conversion (i.e. when // the diagonal recurrent weight matrices are provided as vectors). if (attr.getValue().starts_with("indy_lstm_")) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 17.6K bytes - Viewed (0) -
tensorflow/cc/gradients/linalg_grad.cc
// VJP are einsums with the equations "ji->ij" and "i->ii" respectively, // where the latter represents 'un-tracing', or filling the diagonal with // the input axis and non-diagonal entries are zeros. // Furthermore, recall that matrix multiplication, which is // represented by the equation "ab,bc->ac", has its VJPs given by the
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Mar 07 23:11:54 UTC 2022 - 20.4K bytes - Viewed (0) -
android/guava-tests/test/com/google/common/math/StatsTesting.java
} /** * Asserts that {@code transformation} is diagonal (i.e. neither horizontal nor vertical) and * passes through both {@code (x1, y1)} and {@code (x1 + xDelta, y1 + yDelta)}. Includes * assertions about all the public instance methods of {@link LinearTransformation} (on both * {@code transformation} and its inverse). Since the transformation is expected to be diagonal, * neither {@code xDelta} nor {@code yDelta} may be zero.
Registered: Wed Jun 12 16:38:11 UTC 2024 - Last Modified: Thu Nov 09 22:49:56 UTC 2023 - 22.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/utils/lstm_utils.cc
&recurrent_weights_array))) return failure(); // Reshape recurrent weights to vectors if indy behaviour is enabled. // IndyLSTMs are a LSTM variant with diagonal recurrent weight // matrices. For optimization purposes these are provided as vectors. Value recurrent_to_input_weights = indy ? mlir::cast<Value>(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 36.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/legalize_tf.cc
return success(); } // MatrixDiagV3 is MatrixDiagV2 with an alignment attribute. This attribute // only has effects when processing multiple diagonals. Since TFLite converts // MatrixDiagV{2,3} to MatrixDiag, which only takes single-diagonal inputs, we // can safely ignore this V3 attribute. // We can't pass `rewriter` by reference because clang-tidy will want it to be
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon May 20 20:06:54 UTC 2024 - 45.2K bytes - Viewed (0)