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miaobyte merged 5 commits into from
Apr 23, 2025
Merged

nn.Embedding,IndexSelect,save,load:cpu,cuda 验证 #29

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b7f038a
benchmark.IR:支持对算子进行benchmark
miaobyte Apr 22, 2025
116f9f5
gather,save,load:cuda 验证完成
miaobyte Apr 22, 2025
33ae53b
IndexSelect:测试验证
miaobyte Apr 22, 2025
33ea00f
cuda:load,save,indexselect，和pytorch对齐
miaobyte Apr 23, 2025
ab1269c
nn.module:移除自动注册，改为手动注册tensor、module
miaobyte Apr 23, 2025
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35 changes: 18 additions & 17 deletions doc/excuter/op-mem-cuda/list.md
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Original file line number Diff line number Diff line change
Expand Up @@ -13,10 +13,11 @@

| Operation | Author | Func Def | Math Formula | IR Instruction |
|-----------|--------|------------|--------------|----------------|
| copytensor | none | copytensor(tensor<any> src, tensor<any> dst)->() | T2.data = T1.data | copytensor(tensor<any> src, tensor<any> dst)->() |
| renametensor | none | renametensor(tensor<any> t, var<string> new_name)->() | rename T1 to T2 | renametensor(tensor<any> t, var<string> new_name)->() |
| newtensor | none | newtensor(vector<int32> shape)->(tensor<any> tensor1) | T1 = zeros(shape) | newtensor(vector<int32> shape)->(tensor<any> tensor1) |
| newtensor | none | newtensor(var<string> shape)->(tensor<any> tensor1) | T1 = zeros(shape) | newtensor(var<string> shape)->(tensor<any> tensor1) |
| deltensor | none | deltensor(tensor<any> t)->() | del T1 | deltensor(tensor<any> t)->() |
| copytensor | none | copytensor(tensor<any> src, tensor<any> dst)->() | T2.data = T1.data | copytensor(tensor<any> src, tensor<any> dst)->() |

### io

Expand All @@ -31,9 +32,9 @@

| Operation | Author | Func Def | Math Formula | IR Instruction |
|-----------|--------|------------|--------------|----------------|
| arange | miaobyte | arange(tensor<any> t, var<any> start, var<any> step)->() | arange(T1,start,step) | arange(tensor<any> t, var<any> start, var<any> step)->() |
| normal | miaobyte | normal(tensor<any> t, var<any> mean, var<any> stddev, var<int32> seed)->() | normal(T1,mean,stddev,seed) | normal(tensor<any> t, var<any> mean, var<any> stddev, var<int32> seed)->() |
| uniform | miaobyte | uniform(tensor<any> t, var<any> low, var<any> high, var<int32> seed)->() | uniform(T1,low,high,seed) | uniform(tensor<any> t, var<any> low, var<any> high, var<int32> seed)->() |
| arange | miaobyte | arange(tensor<any> t, var<any> start, var<any> step)->() | arange(T1,start,step) | arange(tensor<any> t, var<any> start, var<any> step)->() |
| constant | miaobyte | constant(tensor<any> t, var<any> value)->() | constant(T1) | constant(tensor<any> t, var<any> value)->() |

### elementwise
Expand All @@ -46,10 +47,10 @@
| min | miaobyte | min(tensor<any> A, tensor<any> B)->(tensor<any> C) | T3=min(T1, T2) | min(tensor<any> A, tensor<any> B)->(tensor<any> C) |
| maxscalar | miaobyte | maxscalar(tensor<any> A, var<any> scalar)->(tensor<any> C) | T3=max(T1, scalar) | maxscalar(tensor<any> A, var<any> scalar)->(tensor<any> C) |
| tan | miaobyte | tan(tensor<float64|float32> A)->(tensor<float64|float32> C) | T3=tan(T1) | tan(tensor<float64|float32> A)->(tensor<float64|float32> C) |
| divscalar | miaobyte | divscalar(tensor<any> A, var<any> scalar)->(tensor<any> C) | T3=scalar/T1 | divscalar(tensor<any> A, var<any> scalar)->(tensor<any> C) |
| sin | miaobyte | sin(tensor<float64|float32|float16|bfloat16> A)->(tensor<float64|float32|float16|bfloat16> C) | T3=sin(T1) | sin(tensor<float64|float32|float16|bfloat16> A)->(tensor<float64|float32|float16|bfloat16> C) |
| add | cublas | add(tensor<any> a, tensor<any> b)->(tensor<any> c) | T3=T1+T2 | add(tensor<any> a, tensor<any> b)->(tensor<any> c) |
| add | miaobyte | add(tensor<any> a, tensor<any> b)->(tensor<any> c) | T3=T1+T2 | add(tensor<any> a, tensor<any> b)->(tensor<any> c) |
| divscalar | miaobyte | divscalar(tensor<any> A, var<any> scalar)->(tensor<any> C) | T3=scalar/T1 | divscalar(tensor<any> A, var<any> scalar)->(tensor<any> C) |
| log | miaobyte | log(tensor<float64|float32|float16|bfloat16> A)->(tensor<float64|float32|float16|bfloat16> C) | T3=log(T1) | log(tensor<float64|float32|float16|bfloat16> A)->(tensor<float64|float32|float16|bfloat16> C) |
| addscalar | miaobyte | addscalar(tensor<any> A, var<any> b)->(tensor<any> C) | T3=T1+scalar | addscalar(tensor<any> A, var<any> b)->(tensor<any> C) |
| greater | miaobyte | greater(tensor<any> A, tensor<any> B)->(tensor<bool> mask) | mask=compare(T1, T2) | greater(tensor<any> A, tensor<any> B)->(tensor<bool> mask) |
| lessscalar | miaobyte | lessscalar(tensor<any> A, var<any> scalar)->(tensor<bool> mask) | mask=compare(T1, scalar) | lessscalar(tensor<any> A, var<any> scalar)->(tensor<bool> mask) |
| cos | miaobyte | cos(tensor<float64|float32|float16|bfloat16> A)->(tensor<float64|float32|float16|bfloat16> C) | T3=cos(T1) | cos(tensor<float64|float32|float16|bfloat16> A)->(tensor<float64|float32|float16|bfloat16> C) |
Expand All @@ -58,8 +59,8 @@
| minscalar | miaobyte | minscalar(tensor<any> A, var<any> scalar)->(tensor<any> C) | T3=min(T1, scalar) | minscalar(tensor<any> A, var<any> scalar)->(tensor<any> C) |
| rdivscalar | miaobyte | rdivscalar(var<any> scalar, tensor<any> A)->(tensor<any> C) | T3=scalar/T1 | rdivscalar(var<any> scalar, tensor<any> A)->(tensor<any> C) |
| rpowscalar | miaobyte | rpowscalar(var<float64|int32> scalar, tensor<float64|float32> A)->(tensor<float64|float32> C) | T3=pow(scalar, T1) | rpowscalar(var<float64|int32> scalar, tensor<float64|float32> A)->(tensor<float64|float32> C) |
| log | miaobyte | log(tensor<float64|float32|float16|bfloat16> A)->(tensor<float64|float32|float16|bfloat16> C) | T3=log(T1) | log(tensor<float64|float32|float16|bfloat16> A)->(tensor<float64|float32|float16|bfloat16> C) |
| addscalar | miaobyte | addscalar(tensor<any> A, var<any> b)->(tensor<any> C) | T3=T1+scalar | addscalar(tensor<any> A, var<any> b)->(tensor<any> C) |
| add | cublas | add(tensor<any> a, tensor<any> b)->(tensor<any> c) | T3=T1+T2 | add(tensor<any> a, tensor<any> b)->(tensor<any> c) |
| add | miaobyte | add(tensor<any> a, tensor<any> b)->(tensor<any> c) | T3=T1+T2 | add(tensor<any> a, tensor<any> b)->(tensor<any> c) |
| sub | miaobyte | sub(tensor<any> A, tensor<any> B)->(tensor<any> C) | T3=T1-T2 | sub(tensor<any> A, tensor<any> B)->(tensor<any> C) |
| sqrt | miaobyte | sqrt(tensor<float64|float32|float16|bfloat16> A)->(tensor<float64|float32|float16|bfloat16> C) | T3=sqrt(T1) | sqrt(tensor<float64|float32|float16|bfloat16> A)->(tensor<float64|float32|float16|bfloat16> C) |
| subscalar | miaobyte | subscalar(tensor<any> A, var<any> b)->(tensor<any> C) | T3=T1-scalar | subscalar(tensor<any> A, var<any> b)->(tensor<any> C) |
Expand All @@ -78,22 +79,22 @@
|-----------|--------|------------|--------------|----------------|
| matmul | cublas | matmul(tensor<any> A, tensor<any> B)->(tensor<any> C) | T3=T1 @ T2 | matmul(tensor<any> A, tensor<any> B)->(tensor<any> C) |

### reduce

| Operation | Author | Func Def | Math Formula | IR Instruction |
|-----------|--------|------------|--------------|----------------|
| prod | miaobyte | prod(tensor<any> A, vector<int32> dims, var<bool> keepdims)->(tensor<any> B) | B = prod(A, axis=[1 2], keepdims=false) | prod(tensor<any> A, vector<int32> dims, var<bool> keepdims)->(tensor<any> B) |
| reducemax | miaobyte | reducemax(tensor<any> A, vector<int32> dims, var<bool> keepdims)->(tensor<any> B) | B = reducemax(A, axis=[1 2], keepdims=false) | reducemax(tensor<any> A, vector<int32> dims, var<bool> keepdims)->(tensor<any> B) |
| sum | miaobyte | sum(tensor<any> A, vector<int32> dims, var<bool> keepdims)->(tensor<any> B) | B = sum(A, axis=[1 2], keepdims=false) | sum(tensor<any> A, vector<int32> dims, var<bool> keepdims)->(tensor<any> B) |
| reducemin | miaobyte | reducemin(tensor<any> A, vector<int32> dims, var<bool> keepdims)->(tensor<any> B) | B = reducemin(A, axis=[1 2], keepdims=false) | reducemin(tensor<any> A, vector<int32> dims, var<bool> keepdims)->(tensor<any> B) |

### changeshape

| Operation | Author | Func Def | Math Formula | IR Instruction |
|-----------|--------|------------|--------------|----------------|
| gather | miaobyte | gather(tensor<any> A, tensor<int64|int32> indices, var<int32> axis)->(tensor<any> B) | T2 = T1.gather(indices=[1,2], axis=1) | gather(tensor<any> A, tensor<int64|int32> indices, var<int32> axis)->(tensor<any> B) |
| indexselect | miaobyte | indexselect(tensor<any> A, tensor<int64|int32> indices, var<int32> axis)->(tensor<any> B) | T2 = T1.indexselect(index=[1,2], axis=1) | indexselect(tensor<any> A, tensor<int64|int32> indices, var<int32> axis)->(tensor<any> B) |
| broadcastTo | miaobyte | broadcastTo(tensor<any> A, vector<int32> new_shape)->(tensor<any> B) | T2 = T1.broadcastTo(new_shape=[4,3,2]) | broadcastTo(tensor<any> A, vector<int32> new_shape)->(tensor<any> B) |
| concat | miaobyte | concat(listtensor<any> tensors, var<int32> dim)->(tensor<any> result) | Tresult = concat([T1, T2...], axis=3) | concat(listtensor<any> tensors, var<int32> dim)->(tensor<any> result) |
| transpose | miaobyte | transpose(tensor<any> A, vector<int32> dim_order)->(tensor<any> C) | T2 = T1.transpose(dimorder=[1,0]) | transpose(tensor<any> A, vector<int32> dim_order)->(tensor<any> C) |
| reshape | miaobyte | reshape(tensor<any> A, vector<int32> shape)->(tensor<any> B) | T1.reshape(shape)->T2 | reshape(tensor<any> A, vector<int32> shape)->(tensor<any> B) |

### reduce

| Operation | Author | Func Def | Math Formula | IR Instruction |
|-----------|--------|------------|--------------|----------------|
| reducemax | miaobyte | reducemax(tensor<any> A, vector<int32> dims, var<bool> keepdims)->(tensor<any> B) | B = reducemax(A, axis=[1 2], keepdims=false) | reducemax(tensor<any> A, vector<int32> dims, var<bool> keepdims)->(tensor<any> B) |
| prod | miaobyte | prod(tensor<any> A, vector<int32> dims, var<bool> keepdims)->(tensor<any> B) | B = prod(A, axis=[1 2], keepdims=false) | prod(tensor<any> A, vector<int32> dims, var<bool> keepdims)->(tensor<any> B) |
| sum | miaobyte | sum(tensor<any> A, vector<int32> dims, var<bool> keepdims)->(tensor<any> B) | B = sum(A, axis=[1 2], keepdims=false) | sum(tensor<any> A, vector<int32> dims, var<bool> keepdims)->(tensor<any> B) |
| reducemin | miaobyte | reducemin(tensor<any> A, vector<int32> dims, var<bool> keepdims)->(tensor<any> B) | B = reducemin(A, axis=[1 2], keepdims=false) | reducemin(tensor<any> A, vector<int32> dims, var<bool> keepdims)->(tensor<any> B) |

35 changes: 18 additions & 17 deletions doc/excuter/op-mem-ompsimd/list.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -13,10 +13,11 @@

| Operation | Author | Func Def | Math Formula | IR Instruction |
|-----------|--------|------------|--------------|----------------|
| copytensor | none | copytensor(tensor<any> src, tensor<any> dst)->() | T2.data = T1.data | copytensor(tensor<any> src, tensor<any> dst)->() |
| renametensor | none | renametensor(tensor<any> t, var<string> new_name)->() | rename T1 to T2 | renametensor(tensor<any> t, var<string> new_name)->() |
| newtensor | none | newtensor(vector<int32> shape)->(tensor<any> tensor1) | T1 =Tensor(shape=[...]) | newtensor(vector<int32> shape)->(tensor<any> tensor1) |
| newtensor | none | newtensor(var<string> shape)->(tensor<any> t) | T1 =Tensor(shape=[...]) | newtensor(var<string> shape)->(tensor<any> t) |
| deltensor | none | deltensor(tensor<any> t)->() | del T1 | deltensor(tensor<any> t)->() |
| copytensor | none | copytensor(tensor<any> src, tensor<any> dst)->() | T2.data = T1.data | copytensor(tensor<any> src, tensor<any> dst)->() |

### io

Expand All @@ -25,15 +26,15 @@
| save | none | save(tensor<any> t, var<string> path)->() | save(T1,path) | save(tensor<any> t, var<string> path)->() |
| print | miaobyte | print(tensor<any> t)->() | print(T1) | print(tensor<any> t)->() |
| print | miaobyte | print(tensor<any> t, var<string> format)->() | print(T1) | print(tensor<any> t, var<string> format)->() |
| load | none | load(var<string> path)->() | load(path) | load(var<string> path)->() |
| load | none | load(var<string> path)->() | mem.load(path) | load(var<string> path)->() |

### init

| Operation | Author | Func Def | Math Formula | IR Instruction |
|-----------|--------|------------|--------------|----------------|
| arange | miaobyte | arange(tensor<any> t, var<any> start, var<any> step)->() | arange(T1,start,step) | arange(tensor<any> t, var<any> start, var<any> step)->() |
| normal | miaobyte | normal(tensor<any> t, var<any> mean, var<any> std, var<int32> seed)->() | normal(T1,mean,stddev,seed) | normal(tensor<any> t, var<any> mean, var<any> std, var<int32> seed)->() |
| uniform | miaobyte | uniform(tensor<any> t, var<any> low, var<any> high, var<int32> seed)->() | uniform(T1,low,high,seed) | uniform(tensor<any> t, var<any> low, var<any> high, var<int32> seed)->() |
| arange | miaobyte | arange(tensor<any> t, var<any> start, var<any> step)->() | arange(T1,start,step) | arange(tensor<any> t, var<any> start, var<any> step)->() |
| constant | miaobyte | constant(tensor<any> t, var<any> value)->() | constant(T1,value) | constant(tensor<any> t, var<any> value)->() |

### elementwise
Expand All @@ -46,17 +47,17 @@
| min | miaobyte | min(tensor<any> A, tensor<any> B)->(tensor<any> C) | T3=min(T1,T2) | min(tensor<any> A, tensor<any> B)->(tensor<any> C) |
| maxscalar | miaobyte | maxscalar(tensor<any> A, var<any> scalar)->(tensor<any> C) | T3=max(T1,scalar) | maxscalar(tensor<any> A, var<any> scalar)->(tensor<any> C) |
| divscalar | miaobyte | divscalar(tensor<any> A, var<any> scalar)->(tensor<any> C) | T3=T1/scalar | divscalar(tensor<any> A, var<any> scalar)->(tensor<any> C) |
| add | cblas | add(tensor<float64|float32> a, tensor<float64|float32> b)->(tensor<float64|float32> c) | T3=T1+T2 | add(tensor<float64|float32> a, tensor<float64|float32> b)->(tensor<float64|float32> c) |
| add | miaobyte | add(tensor<any> a, tensor<any> b)->(tensor<any> c) | T3=T1+T2 | add(tensor<any> a, tensor<any> b)->(tensor<any> c) |
| log | miaobyte | log(tensor<any> A)->(tensor<any> C) | T3=log(T1) | log(tensor<any> A)->(tensor<any> C) |
| addscalar | miaobyte | addscalar(tensor<any> a, var<any> scalar)->(tensor<any> c) | T3=T1+scalar | addscalar(tensor<any> a, var<any> scalar)->(tensor<any> c) |
| greater | miaobyte | greater(tensor<any> A, tensor<any> B)->(tensor<bool> mask) | mask=greater(T1,T2) | greater(tensor<any> A, tensor<any> B)->(tensor<bool> mask) |
| lessscalar | miaobyte | lessscalar(tensor<any> A, var<any> scalar)->(tensor<bool> mask) | mask=less(T1,scalar) | lessscalar(tensor<any> A, var<any> scalar)->(tensor<bool> mask) |
| less | miaobyte | less(tensor<any> A, tensor<any> B)->(tensor<bool> mask) | mask=less(T1,T2) | less(tensor<any> A, tensor<any> B)->(tensor<bool> mask) |
| powscalar | miaobyte | powscalar(tensor<any> A, var<any> scalar)->(tensor<any> C) | T3=T1^scalar | powscalar(tensor<any> A, var<any> scalar)->(tensor<any> C) |
| minscalar | miaobyte | minscalar(tensor<any> A, var<any> scalar)->(tensor<any> C) | T3=min(T1,scalar) | minscalar(tensor<any> A, var<any> scalar)->(tensor<any> C) |
| rdivscalar | miaobyte | rdivscalar(var<any> scalar, tensor<any> A)->(tensor<any> C) | T3=scalar/T1 | rdivscalar(var<any> scalar, tensor<any> A)->(tensor<any> C) |
| rpowscalar | miaobyte | rpowscalar(var<any> scalar, tensor<any> A)->(tensor<any> C) | T3=scalar^T1 | rpowscalar(var<any> scalar, tensor<any> A)->(tensor<any> C) |
| log | miaobyte | log(tensor<any> A)->(tensor<any> C) | T3=log(T1) | log(tensor<any> A)->(tensor<any> C) |
| addscalar | miaobyte | addscalar(tensor<any> a, var<any> scalar)->(tensor<any> c) | T3=T1+scalar | addscalar(tensor<any> a, var<any> scalar)->(tensor<any> c) |
| add | cblas | add(tensor<float64|float32> a, tensor<float64|float32> b)->(tensor<float64|float32> c) | T3=T1+T2 | add(tensor<float64|float32> a, tensor<float64|float32> b)->(tensor<float64|float32> c) |
| add | miaobyte | add(tensor<any> a, tensor<any> b)->(tensor<any> c) | T3=T1+T2 | add(tensor<any> a, tensor<any> b)->(tensor<any> c) |
| sub | miaobyte | sub(tensor<any> a, tensor<any> b)->(tensor<any> c) | T3=T1-T2 | sub(tensor<any> a, tensor<any> b)->(tensor<any> c) |
| sqrt | miaobyte | sqrt(tensor<any> A)->(tensor<any> C) | T3=sqrt(T1) | sqrt(tensor<any> A)->(tensor<any> C) |
| subscalar | miaobyte | subscalar(tensor<any> a, var<any> scalar)->(tensor<any> c) | T3=T1-scalar | subscalar(tensor<any> a, var<any> scalar)->(tensor<any> c) |
Expand All @@ -76,22 +77,22 @@
| matmul | cblas | matmul(tensor<float64|float32> A, tensor<float64|float32> B)->(tensor<float64|float32> C) | T3=T1 @ T2 | matmul(tensor<float64|float32> A, tensor<float64|float32> B)->(tensor<float64|float32> C) |
| matmul | miaobyte | matmul(tensor<any> A, tensor<any> B)->(tensor<any> C) | T3=T1 @ T2 | matmul(tensor<any> A, tensor<any> B)->(tensor<any> C) |

### reduce

| Operation | Author | Func Def | Math Formula | IR Instruction |
|-----------|--------|------------|--------------|----------------|
| prod | miaobyte | prod(tensor<any> A, vector<int32> axis, var<bool> keepdims)->(tensor<any> B) | B = prod(A, axis=[1 2], keepdims=false) | prod(tensor<any> A, vector<int32> axis, var<bool> keepdims)->(tensor<any> B) |
| reducemax | miaobyte | reducemax(tensor<any> A, vector<int32> axis, var<bool> keepdims)->(tensor<any> B) | B = reducemax(A, axis=[1 2], keepdims=false) | reducemax(tensor<any> A, vector<int32> axis, var<bool> keepdims)->(tensor<any> B) |
| sum | miaobyte | sum(tensor<any> A, vector<int32> axis, var<bool> keepdims)->(tensor<any> B) | B = sum(A, axis=[1 2], keepdims=false) | sum(tensor<any> A, vector<int32> axis, var<bool> keepdims)->(tensor<any> B) |
| reducemin | miaobyte | reducemin(tensor<any> A, vector<int32> axis, var<bool> keepdims)->(tensor<any> B) | B = reducemin(A, axis=[1 2], keepdims=false) | reducemin(tensor<any> A, vector<int32> axis, var<bool> keepdims)->(tensor<any> B) |

### changeshape

| Operation | Author | Func Def | Math Formula | IR Instruction |
|-----------|--------|------------|--------------|----------------|
| gather | miaobyte | gather(tensor<any> A, tensor<int64|int32> indices, var<int32> axis)->(tensor<any> B) | T2 = T1.gather(indices=T3, axis=3) | gather(tensor<any> A, tensor<int64|int32> indices, var<int32> axis)->(tensor<any> B) |
| indexselect | miaobyte | indexselect(tensor<any> A, tensor<int64|int32> index, var<int32> axis)->(tensor<any> B) | T2 = T1.indexselect(index=T3, axis=3) | indexselect(tensor<any> A, tensor<int64|int32> index, var<int32> axis)->(tensor<any> B) |
| broadcastTo | miaobyte | broadcastTo(tensor<any> A, vector<int32> new_shape)->(tensor<any> B) | T2 = T1.broadcastTo(new_shape=[4,3,2]) | broadcastTo(tensor<any> A, vector<int32> new_shape)->(tensor<any> B) |
| concat | miaobyte | concat(listtensor<any> tensors, var<int32> dim)->(tensor<any> result) | Tresult = concat([T1, T2...], axis=3) | concat(listtensor<any> tensors, var<int32> dim)->(tensor<any> result) |
| transpose | miaobyte | transpose(tensor<any> A, vector<int32> dim_order)->(tensor<any> C) | T1.transpose(dimorder=[1,0])->T2 | transpose(tensor<any> A, vector<int32> dim_order)->(tensor<any> C) |
| reshape | miaobyte | reshape(tensor<any> A, vector<int32> shape)->(tensor<any> B) | T1.reshape(shape)->T2 | reshape(tensor<any> A, vector<int32> shape)->(tensor<any> B) |

### reduce

| Operation | Author | Func Def | Math Formula | IR Instruction |
|-----------|--------|------------|--------------|----------------|
| reducemax | miaobyte | reducemax(tensor<any> A, vector<int32> axis, var<bool> keepdims)->(tensor<any> B) | B = reducemax(A, axis=[1 2], keepdims=false) | reducemax(tensor<any> A, vector<int32> axis, var<bool> keepdims)->(tensor<any> B) |
| prod | miaobyte | prod(tensor<any> A, vector<int32> axis, var<bool> keepdims)->(tensor<any> B) | B = prod(A, axis=[1 2], keepdims=false) | prod(tensor<any> A, vector<int32> axis, var<bool> keepdims)->(tensor<any> B) |
| sum | miaobyte | sum(tensor<any> A, vector<int32> axis, var<bool> keepdims)->(tensor<any> B) | B = sum(A, axis=[1 2], keepdims=false) | sum(tensor<any> A, vector<int32> axis, var<bool> keepdims)->(tensor<any> B) |
| reducemin | miaobyte | reducemin(tensor<any> A, vector<int32> axis, var<bool> keepdims)->(tensor<any> B) | B = reducemin(A, axis=[1 2], keepdims=false) | reducemin(tensor<any> A, vector<int32> axis, var<bool> keepdims)->(tensor<any> B) |

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