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voltjia merged 3 commits into from
Jul 31, 2026
Merged

fix: support InfiniRT metadata views #828

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701120b
fix: support InfiniRT metadata views
voltjia Jul 28, 2026
ae1f760
test: complete metadata view regression fixture
voltjia Jul 28, 2026
da9f5e5
test: include returning operator fixtures
voltjia Jul 28, 2026
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4 changes: 2 additions & 2 deletions scripts/generate_torch_ops.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1118,11 +1118,11 @@ def _generate_base_header(name: str, ops: list[Op]) -> str:
init_pieces.append(f" has_{api_name}_{{{api_name}.has_value()}}")
init_pieces.append(
f" {api_name}_shape_{{{api_name} ? "
f"{api_name}->shape() : Tensor::Shape{{}}}}"
f"Tensor::Shape{{{api_name}->shape()}} : Tensor::Shape{{}}}}"
)
init_pieces.append(
f" {api_name}_strides_{{{api_name} ? "
f"{api_name}->strides() : Tensor::Strides{{}}}}"
f"Tensor::Strides{{{api_name}->strides()}} : Tensor::Strides{{}}}}"
)
init_pieces.append(
f" {api_name}_type_{{{api_name} ? "
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3 changes: 1 addition & 2 deletions src/base/add.h
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Expand Up @@ -4,7 +4,6 @@
#include <algorithm>
#include <cstddef>
#include <cstdint>
#include <vector>

#include "operator.h"

Expand Down Expand Up @@ -68,7 +67,7 @@ class Add : public Operator<Add> {
auto input_shape = input.shape();
auto other_shape = other.shape();
auto ndim = std::max(input_shape.size(), other_shape.size());
std::vector<std::size_t> out_shape(ndim, 1);
typename TensorLike::Shape out_shape(ndim, 1);

for (std::size_t i = 0; i < ndim; ++i) {
auto input_dim = i < ndim - input_shape.size()
Expand Down
11 changes: 7 additions & 4 deletions src/base/batch_norm_elemt.h
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Expand Up @@ -25,12 +25,15 @@ class BatchNormElemt : public Operator<BatchNormElemt> {
out_strides_{out.strides()},
out_type_{out.dtype()},
has_weight_{weight.has_value()},
weight_shape_{weight ? weight->shape() : Tensor::Shape{}},
weight_strides_{weight ? weight->strides() : Tensor::Strides{}},
weight_shape_{weight ? Tensor::Shape{weight->shape()}
: Tensor::Shape{}},
weight_strides_{weight ? Tensor::Strides{weight->strides()}
: Tensor::Strides{}},
weight_type_{weight ? weight->dtype() : DataType::kFloat32},
has_bias_{bias.has_value()},
bias_shape_{bias ? bias->shape() : Tensor::Shape{}},
bias_strides_{bias ? bias->strides() : Tensor::Strides{}},
bias_shape_{bias ? Tensor::Shape{bias->shape()} : Tensor::Shape{}},
bias_strides_{bias ? Tensor::Strides{bias->strides()}
: Tensor::Strides{}},
bias_type_{bias ? bias->dtype() : DataType::kFloat32},
eps_{eps},
device_index_{out.device().index()} {}
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6 changes: 4 additions & 2 deletions src/base/binary_cross_entropy.h
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Expand Up @@ -22,8 +22,10 @@ class BinaryCrossEntropy : public Operator<BinaryCrossEntropy> {
out_strides_{out.strides()},
out_type_{out.dtype()},
has_weight_{weight.has_value()},
weight_shape_{weight ? weight->shape() : Tensor::Shape{}},
weight_strides_{weight ? weight->strides() : Tensor::Strides{}},
weight_shape_{weight ? Tensor::Shape{weight->shape()}
: Tensor::Shape{}},
weight_strides_{weight ? Tensor::Strides{weight->strides()}
: Tensor::Strides{}},
weight_type_{weight ? weight->dtype() : DataType::kFloat32},
reduction_{reduction},
device_index_{out.device().index()} {}
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6 changes: 4 additions & 2 deletions src/base/binary_cross_entropy_backward.h
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Expand Up @@ -26,8 +26,10 @@ class BinaryCrossEntropyBackward : public Operator<BinaryCrossEntropyBackward> {
grad_input_strides_{grad_input.strides()},
grad_input_type_{grad_input.dtype()},
has_weight_{weight.has_value()},
weight_shape_{weight ? weight->shape() : Tensor::Shape{}},
weight_strides_{weight ? weight->strides() : Tensor::Strides{}},
weight_shape_{weight ? Tensor::Shape{weight->shape()}
: Tensor::Shape{}},
weight_strides_{weight ? Tensor::Strides{weight->strides()}
: Tensor::Strides{}},
weight_type_{weight ? weight->dtype() : DataType::kFloat32},
reduction_{reduction},
device_index_{grad_input.device().index()} {}
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8 changes: 4 additions & 4 deletions src/base/clamp.h
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Expand Up @@ -30,12 +30,12 @@ class Clamp : public Operator<Clamp> {
out_strides_{out.strides()},
out_type_{out.dtype()},
has_min_{min.has_value()},
min_shape_{min ? min->shape() : Tensor::Shape{}},
min_strides_{min ? min->strides() : Tensor::Strides{}},
min_shape_{min ? Tensor::Shape{min->shape()} : Tensor::Shape{}},
min_strides_{min ? Tensor::Strides{min->strides()} : Tensor::Strides{}},
min_type_{min ? min->dtype() : DataType::kFloat32},
has_max_{max.has_value()},
max_shape_{max ? max->shape() : Tensor::Shape{}},
max_strides_{max ? max->strides() : Tensor::Strides{}},
max_shape_{max ? Tensor::Shape{max->shape()} : Tensor::Shape{}},
max_strides_{max ? Tensor::Strides{max->strides()} : Tensor::Strides{}},
max_type_{max ? max->dtype() : DataType::kFloat32},
device_index_{out.device().index()} {}

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8 changes: 4 additions & 4 deletions src/base/clip.h
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Expand Up @@ -30,12 +30,12 @@ class Clip : public Operator<Clip> {
out_strides_{out.strides()},
out_type_{out.dtype()},
has_min_{min.has_value()},
min_shape_{min ? min->shape() : Tensor::Shape{}},
min_strides_{min ? min->strides() : Tensor::Strides{}},
min_shape_{min ? Tensor::Shape{min->shape()} : Tensor::Shape{}},
min_strides_{min ? Tensor::Strides{min->strides()} : Tensor::Strides{}},
min_type_{min ? min->dtype() : DataType::kFloat32},
has_max_{max.has_value()},
max_shape_{max ? max->shape() : Tensor::Shape{}},
max_strides_{max ? max->strides() : Tensor::Strides{}},
max_shape_{max ? Tensor::Shape{max->shape()} : Tensor::Shape{}},
max_strides_{max ? Tensor::Strides{max->strides()} : Tensor::Strides{}},
max_type_{max ? max->dtype() : DataType::kFloat32},
device_index_{out.device().index()} {}

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6 changes: 4 additions & 2 deletions src/base/conv_infinilm.h
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Expand Up @@ -23,8 +23,10 @@ class ConvInfinilm : public Operator<ConvInfinilm> {
weight_strides_{weight.strides()},
out_shape_{out.shape()},
out_strides_{out.strides()},
bias_shape_{bias.has_value() ? bias->shape() : Tensor::Shape{}},
bias_strides_{bias.has_value() ? bias->strides() : Tensor::Strides{}},
bias_shape_{bias.has_value() ? Tensor::Shape{bias->shape()}
: Tensor::Shape{}},
bias_strides_{bias.has_value() ? Tensor::Strides{bias->strides()}
: Tensor::Strides{}},
input_type_{input.dtype()},
weight_type_{weight.dtype()},
out_type_{out.dtype()},
Expand Down
12 changes: 8 additions & 4 deletions src/base/diff.h
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Expand Up @@ -19,12 +19,16 @@ class Diff : public Operator<Diff> {
out_strides_{out.strides()},
out_type_{out.dtype()},
has_prepend_{prepend.has_value()},
prepend_shape_{prepend ? prepend->shape() : Tensor::Shape{}},
prepend_strides_{prepend ? prepend->strides() : Tensor::Strides{}},
prepend_shape_{prepend ? Tensor::Shape{prepend->shape()}
: Tensor::Shape{}},
prepend_strides_{prepend ? Tensor::Strides{prepend->strides()}
: Tensor::Strides{}},
prepend_type_{prepend ? prepend->dtype() : DataType::kFloat32},
has_append_{append.has_value()},
append_shape_{append ? append->shape() : Tensor::Shape{}},
append_strides_{append ? append->strides() : Tensor::Strides{}},
append_shape_{append ? Tensor::Shape{append->shape()}
: Tensor::Shape{}},
append_strides_{append ? Tensor::Strides{append->strides()}
: Tensor::Strides{}},
append_type_{append ? append->dtype() : DataType::kFloat32},
n_{n},
dim_{dim},
Expand Down
2 changes: 1 addition & 1 deletion src/base/embedding.h
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Expand Up @@ -101,7 +101,7 @@ class Embedding : public Operator<Embedding> {
const double /*norm_type*/ = 2.0,
const bool /*scale_grad_by_freq*/ = false,
const bool /*sparse*/ = false) {
auto out_shape = input.shape();
typename TensorLike::Shape out_shape{input.shape()};
out_shape.push_back(weight.size(1));

return TensorLike::Empty(out_shape, weight.dtype(), weight.device());
Expand Down
73 changes: 43 additions & 30 deletions src/base/flash_attn_with_kvcache.h
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Expand Up @@ -90,46 +90,59 @@ class FlashAttnWithKvcache : public Operator<FlashAttnWithKvcache> {
: q_shape_{q.shape()},
k_cache_shape_{k_cache.shape()},
v_cache_shape_{v_cache.shape()},
k_shape_{k.has_value() ? k->shape() : Tensor::Shape{}},
v_shape_{v.has_value() ? v->shape() : Tensor::Shape{}},
rotary_cos_shape_{rotary_cos.has_value() ? rotary_cos->shape()
: Tensor::Shape{}},
rotary_sin_shape_{rotary_sin.has_value() ? rotary_sin->shape()
: Tensor::Shape{}},
cache_seqlens_shape_{cache_seqlens.has_value() ? cache_seqlens->shape()
: Tensor::Shape{}},
k_shape_{k.has_value() ? Tensor::Shape{k->shape()} : Tensor::Shape{}},
v_shape_{v.has_value() ? Tensor::Shape{v->shape()} : Tensor::Shape{}},
rotary_cos_shape_{rotary_cos.has_value()
? Tensor::Shape{rotary_cos->shape()}
: Tensor::Shape{}},
rotary_sin_shape_{rotary_sin.has_value()
? Tensor::Shape{rotary_sin->shape()}
: Tensor::Shape{}},
cache_seqlens_shape_{cache_seqlens.has_value()
? Tensor::Shape{cache_seqlens->shape()}
: Tensor::Shape{}},
cache_batch_idx_shape_{cache_batch_idx.has_value()
? cache_batch_idx->shape()
? Tensor::Shape{cache_batch_idx->shape()}
: Tensor::Shape{}},
cache_leftpad_shape_{cache_leftpad.has_value() ? cache_leftpad->shape()
: Tensor::Shape{}},
block_table_shape_{block_table.has_value() ? block_table->shape()
: Tensor::Shape{}},
alibi_slopes_shape_{alibi_slopes.has_value() ? alibi_slopes->shape()
: Tensor::Shape{}},
cache_leftpad_shape_{cache_leftpad.has_value()
? Tensor::Shape{cache_leftpad->shape()}
: Tensor::Shape{}},
block_table_shape_{block_table.has_value()
? Tensor::Shape{block_table->shape()}
: Tensor::Shape{}},
alibi_slopes_shape_{alibi_slopes.has_value()
? Tensor::Shape{alibi_slopes->shape()}
: Tensor::Shape{}},
out_shape_{out.shape()},
q_strides_{q.strides()},
k_cache_strides_{k_cache.strides()},
v_cache_strides_{v_cache.strides()},
k_strides_{k.has_value() ? k->strides() : Tensor::Strides{}},
v_strides_{v.has_value() ? v->strides() : Tensor::Strides{}},
rotary_cos_strides_{rotary_cos.has_value() ? rotary_cos->strides()
: Tensor::Strides{}},
rotary_sin_strides_{rotary_sin.has_value() ? rotary_sin->strides()
: Tensor::Strides{}},
k_strides_{k.has_value() ? Tensor::Strides{k->strides()}
: Tensor::Strides{}},
v_strides_{v.has_value() ? Tensor::Strides{v->strides()}
: Tensor::Strides{}},
rotary_cos_strides_{rotary_cos.has_value()
? Tensor::Strides{rotary_cos->strides()}
: Tensor::Strides{}},
rotary_sin_strides_{rotary_sin.has_value()
? Tensor::Strides{rotary_sin->strides()}
: Tensor::Strides{}},
cache_seqlens_strides_{cache_seqlens.has_value()
? cache_seqlens->strides()
? Tensor::Strides{cache_seqlens->strides()}
: Tensor::Strides{}},
cache_batch_idx_strides_{cache_batch_idx.has_value()
? cache_batch_idx->strides()
: Tensor::Strides{}},
cache_batch_idx_strides_{
cache_batch_idx.has_value()
? Tensor::Strides{cache_batch_idx->strides()}
: Tensor::Strides{}},
cache_leftpad_strides_{cache_leftpad.has_value()
? cache_leftpad->strides()
? Tensor::Strides{cache_leftpad->strides()}
: Tensor::Strides{}},
block_table_strides_{block_table.has_value() ? block_table->strides()
: Tensor::Strides{}},
alibi_slopes_strides_{alibi_slopes.has_value() ? alibi_slopes->strides()
: Tensor::Strides{}},
block_table_strides_{block_table.has_value()
? Tensor::Strides{block_table->strides()}
: Tensor::Strides{}},
alibi_slopes_strides_{alibi_slopes.has_value()
? Tensor::Strides{alibi_slopes->strides()}
: Tensor::Strides{}},
out_strides_{out.strides()},
q_dtype_{q.dtype()},
k_cache_dtype_{k_cache.dtype()},
Expand Down
12 changes: 8 additions & 4 deletions src/base/histogram.h
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Expand Up @@ -26,8 +26,10 @@ class Histogram : public Operator<Histogram> {
bin_edges_strides_{bin_edges.strides()},
bin_edges_type_{bin_edges.dtype()},
has_weight_{weight.has_value()},
weight_shape_{weight ? weight->shape() : Tensor::Shape{}},
weight_strides_{weight ? weight->strides() : Tensor::Strides{}},
weight_shape_{weight ? Tensor::Shape{weight->shape()}
: Tensor::Shape{}},
weight_strides_{weight ? Tensor::Strides{weight->strides()}
: Tensor::Strides{}},
weight_type_{weight ? weight->dtype() : DataType::kFloat32},
density_{density},
device_index_{hist.device().index()} {}
Expand All @@ -46,8 +48,10 @@ class Histogram : public Operator<Histogram> {
bin_edges_strides_{bin_edges.strides()},
bin_edges_type_{bin_edges.dtype()},
has_weight_{weight.has_value()},
weight_shape_{weight ? weight->shape() : Tensor::Shape{}},
weight_strides_{weight ? weight->strides() : Tensor::Strides{}},
weight_shape_{weight ? Tensor::Shape{weight->shape()}
: Tensor::Shape{}},
weight_strides_{weight ? Tensor::Strides{weight->strides()}
: Tensor::Strides{}},
weight_type_{weight ? weight->dtype() : DataType::kFloat32},
density_{density},
bins_{bins},
Expand Down
11 changes: 7 additions & 4 deletions src/base/internal_batch_norm_with_update.h
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Expand Up @@ -36,12 +36,15 @@ class BatchNormWithUpdate : public Operator<BatchNormWithUpdate> {
reserve_strides_{reserve.strides()},
reserve_type_{reserve.dtype()},
has_weight_{weight.has_value()},
weight_shape_{weight ? weight->shape() : Tensor::Shape{}},
weight_strides_{weight ? weight->strides() : Tensor::Strides{}},
weight_shape_{weight ? Tensor::Shape{weight->shape()}
: Tensor::Shape{}},
weight_strides_{weight ? Tensor::Strides{weight->strides()}
: Tensor::Strides{}},
weight_type_{weight ? weight->dtype() : DataType::kFloat32},
has_bias_{bias.has_value()},
bias_shape_{bias ? bias->shape() : Tensor::Shape{}},
bias_strides_{bias ? bias->strides() : Tensor::Strides{}},
bias_shape_{bias ? Tensor::Shape{bias->shape()} : Tensor::Shape{}},
bias_strides_{bias ? Tensor::Strides{bias->strides()}
: Tensor::Strides{}},
bias_type_{bias ? bias->dtype() : DataType::kFloat32},
momentum_{momentum},
eps_{eps},
Expand Down
5 changes: 3 additions & 2 deletions src/base/internal_conv_depthwise2d.h
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Expand Up @@ -26,8 +26,9 @@ class ConvDepthwise2d : public Operator<ConvDepthwise2d> {
out_strides_{out.strides()},
out_type_{out.dtype()},
has_bias_{bias.has_value()},
bias_shape_{bias ? bias->shape() : Tensor::Shape{}},
bias_strides_{bias ? bias->strides() : Tensor::Strides{}},
bias_shape_{bias ? Tensor::Shape{bias->shape()} : Tensor::Shape{}},
bias_strides_{bias ? Tensor::Strides{bias->strides()}
: Tensor::Strides{}},
bias_type_{bias ? bias->dtype() : DataType::kFloat32},
kernel_size_{kernel_size},
stride_{stride},
Expand Down
22 changes: 14 additions & 8 deletions src/base/internal_native_batch_norm_legit.h
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Expand Up @@ -33,12 +33,15 @@ class NativeBatchNormLegit : public Operator<NativeBatchNormLegit> {
save_invstd_strides_{save_invstd.strides()},
save_invstd_type_{save_invstd.dtype()},
has_weight_{weight.has_value()},
weight_shape_{weight ? weight->shape() : Tensor::Shape{}},
weight_strides_{weight ? weight->strides() : Tensor::Strides{}},
weight_shape_{weight ? Tensor::Shape{weight->shape()}
: Tensor::Shape{}},
weight_strides_{weight ? Tensor::Strides{weight->strides()}
: Tensor::Strides{}},
weight_type_{weight ? weight->dtype() : DataType::kFloat32},
has_bias_{bias.has_value()},
bias_shape_{bias ? bias->shape() : Tensor::Shape{}},
bias_strides_{bias ? bias->strides() : Tensor::Strides{}},
bias_shape_{bias ? Tensor::Shape{bias->shape()} : Tensor::Shape{}},
bias_strides_{bias ? Tensor::Strides{bias->strides()}
: Tensor::Strides{}},
bias_type_{bias ? bias->dtype() : DataType::kFloat32},
training_{training},
momentum_{momentum},
Expand All @@ -62,12 +65,15 @@ class NativeBatchNormLegit : public Operator<NativeBatchNormLegit> {
save_invstd_strides_{save_invstd.strides()},
save_invstd_type_{save_invstd.dtype()},
has_weight_{weight.has_value()},
weight_shape_{weight ? weight->shape() : Tensor::Shape{}},
weight_strides_{weight ? weight->strides() : Tensor::Strides{}},
weight_shape_{weight ? Tensor::Shape{weight->shape()}
: Tensor::Shape{}},
weight_strides_{weight ? Tensor::Strides{weight->strides()}
: Tensor::Strides{}},
weight_type_{weight ? weight->dtype() : DataType::kFloat32},
has_bias_{bias.has_value()},
bias_shape_{bias ? bias->shape() : Tensor::Shape{}},
bias_strides_{bias ? bias->strides() : Tensor::Strides{}},
bias_shape_{bias ? Tensor::Shape{bias->shape()} : Tensor::Shape{}},
bias_strides_{bias ? Tensor::Strides{bias->strides()}
: Tensor::Strides{}},
bias_type_{bias ? bias->dtype() : DataType::kFloat32},
training_{training},
momentum_{momentum},
Expand Down
5 changes: 3 additions & 2 deletions src/base/internal_slow_conv2d_forward.h
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Expand Up @@ -25,8 +25,9 @@ class SlowConv2dForward : public Operator<SlowConv2dForward> {
output_strides_{output.strides()},
output_type_{output.dtype()},
has_bias_{bias.has_value()},
bias_shape_{bias ? bias->shape() : Tensor::Shape{}},
bias_strides_{bias ? bias->strides() : Tensor::Strides{}},
bias_shape_{bias ? Tensor::Shape{bias->shape()} : Tensor::Shape{}},
bias_strides_{bias ? Tensor::Strides{bias->strides()}
: Tensor::Strides{}},
bias_type_{bias ? bias->dtype() : DataType::kFloat32},
kernel_size_{kernel_size},
stride_{stride},
Expand Down
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