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Update CONTRIBOP.MD FP16 support for MatMulIntegerToFloat #18751

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Dec 13, 2023
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Update CONTRIBOP.MD FP16 support for MatMulIntegerToFloat #18751

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3 changes: 1 addition & 2 deletions docs/ContribOperators.md
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Original file line number Diff line number Diff line change
Expand Up @@ -2780,7 +2780,7 @@ This version of the operator has been available since version 1 of the 'com.micr
<dd>Constrain input A data type to 8-bit integer tensor.</dd>
<dt><tt>T2</tt> : tensor(int8), tensor(uint8)</dt>
<dd>Constrain input B data type to 8-bit integer tensor.</dd>
<dt><tt>T3</tt> : tensor(float)</dt>
<dt><tt>T3</tt> : tensor(float), tensor(float16)</dt>
<dd>Constrain input a_scale, b_scale and output Y data type as float tensor.</dd>
</dl>

Expand Down Expand Up @@ -5926,4 +5926,3 @@ No versioning maintained for experimental ops.
<dd>Constrain input and output types to float32 tensors.</dd>
</dl>


20 changes: 14 additions & 6 deletions docs/OperatorKernels.md
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Original file line number Diff line number Diff line change
Expand Up @@ -901,7 +901,8 @@ Do not modify directly.*
|Asinh|*in* input:**T**<br> *out* output:**T**|9+|**T** = tensor(float), tensor(float16)|
|Atan|*in* input:**T**<br> *out* output:**T**|7+|**T** = tensor(float), tensor(float16)|
|Atanh|*in* input:**T**<br> *out* output:**T**|9+|**T** = tensor(float), tensor(float16)|
|AveragePool|*in* X:**T**<br> *out* Y:**T**|11+|**T** = tensor(float), tensor(float16)|
|AveragePool|*in* X:**T**<br> *out* Y:**T**|19+|**T** = tensor(float), tensor(float16)|
|||11+|**T** = tensor(float), tensor(float16)|
|||10+|**T** = tensor(float), tensor(float16)|
|||7+|**T** = tensor(float), tensor(float16)|
|BatchNormalization|*in* X:**T**<br> *in* scale:**T**<br> *in* B:**T**<br> *in* input_mean:**U**<br> *in* input_var:**U**<br> *out* Y:**T**<br> *out* running_mean:**U**<br> *out* running_var:**U**<br><br>or<br><br>*in* X:**T**<br> *in* scale:**T**<br> *in* B:**T**<br> *in* mean:**T**<br> *in* var:**T**<br> *out* Y:**T**<br> *out* mean:**T**<br> *out* var:**T**<br> *out* saved_mean:**T**<br> *out* saved_var:**T**<br><br>or<br><br>*in* X:**T**<br> *in* scale:**T1**<br> *in* B:**T1**<br> *in* input_mean:**T2**<br> *in* input_var:**T2**<br> *out* Y:**T**<br> *out* running_mean:**T2**<br> *out* running_var:**T2**|15+|**T** = tensor(float), tensor(float16)|
Expand Down Expand Up @@ -949,7 +950,7 @@ Do not modify directly.*
|||13+|**T** = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|
|||7+|**T** = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|
|Dropout|*in* data:**T**<br> *in* ratio:**T1**<br> *in* training_mode:**T2**<br> *out* output:**T**<br> *out* mask:**T2**<br><br>or<br><br>*in* data:**T**<br> *out* output:**T**<br> *out* mask:**T**<br><br>or<br><br>*in* data:**T**<br> *out* output:**T**<br> *out* mask:**T1**|7+|**T** = tensor(float), tensor(float16)|
|DynamicQuantizeLinear|*in* x:**T1**<br> *out* y:**T2**<br> *out* y_scale:**tensor(float)**<br> *out* y_zero_point:**T2**|11+|**T1** = tensor(float)<br/> **T2** = tensor(uint8)|
|DynamicQuantizeLinear|*in* x:**T1**<br> *out* y:**T2**<br> *out* y_scale:**tensor(float)**<br> *out* y_zero_point:**T2**|11+|**T1** = tensor(float)<br/> **T2** = tensor(int8), tensor(uint8)|
|Einsum|*in* Inputs:**T**<br> *out* Output:**T**|12+|**T** = tensor(float), tensor(float16)|
|Elu|*in* X:**T**<br> *out* Y:**T**|6+|**T** = tensor(float), tensor(float16)|
|Equal|*in* A:**T**<br> *in* B:**T**<br> *out* C:**T1**|13+|**T** = tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)<br/> **T1** = tensor(bool)|
Expand Down Expand Up @@ -1028,7 +1029,8 @@ Do not modify directly.*
|||11+|**T** = tensor(float), tensor(float16)|
|||1+|**T** = tensor(float), tensor(float16)|
|LpNormalization|*in* input:**T**<br> *out* output:**T**|1+|**T** = tensor(float), tensor(float16)|
|LpPool|*in* X:**T**<br> *out* Y:**T**|11+|**T** = tensor(float), tensor(float16)|
|LpPool|*in* X:**T**<br> *out* Y:**T**|18+|**T** = tensor(float), tensor(float16)|
|||11+|**T** = tensor(float), tensor(float16)|
|||2+|**T** = tensor(float), tensor(float16)|
|MatMul|*in* A:**T**<br> *in* B:**T**<br> *out* Y:**T**|13+|**T** = tensor(float), tensor(float16)|
|||9+|**T** = tensor(float), tensor(float16)|
Expand Down Expand Up @@ -1143,8 +1145,8 @@ Do not modify directly.*
|Reshape|*in* data:**T**<br> *in* shape:**tensor(int64)**<br> *out* reshaped:**T**<br><br>or<br><br>*in* data:**T**<br> *out* reshaped:**T**|14+|**T** = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|
|||13+|**T** = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|
|||5+|**T** = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|
|Resize|*in* X:**T**<br> *in* scales:**tensor(float)**<br> *out* Y:**T**<br><br>or<br><br>*in* X:**T1**<br> *in* roi:**T2**<br> *in* scales:**tensor(float)**<br> *in* sizes:**tensor(int64)**<br> *out* Y:**T1**|13+|**T1** = tensor(float), tensor(float16)<br/> **T2** = tensor(float), tensor(float16)|
|||11+|**T1** = tensor(float), tensor(float16)<br/> **T2** = tensor(float), tensor(float16)|
|Resize|*in* X:**T**<br> *in* scales:**tensor(float)**<br> *out* Y:**T**<br><br>or<br><br>*in* X:**T1**<br> *in* roi:**T2**<br> *in* scales:**tensor(float)**<br> *in* sizes:**tensor(int64)**<br> *out* Y:**T1**|13+|**T1** = tensor(float), tensor(float16), tensor(int8), tensor(uint8)<br/> **T2** = tensor(float), tensor(float16)|
|||11+|**T1** = tensor(float), tensor(float16), tensor(int8), tensor(uint8)<br/> **T2** = tensor(float), tensor(float16)|
|||10+|**T** = tensor(float), tensor(float16)|
|ReverseSequence|*in* input:**T**<br> *in* sequence_lens:**tensor(int64)**<br> *out* Y:**T**|10+|**T** = tensor(bool), tensor(double), tensor(float), tensor(float16), tensor(int16), tensor(int32), tensor(int64), tensor(int8), tensor(uint16), tensor(uint32), tensor(uint64), tensor(uint8)|
|RoiAlign|*in* X:**T1**<br> *in* rois:**T1**<br> *in* batch_indices:**T2**<br> *out* Y:**T1**|16+|**T1** = tensor(float), tensor(float16)<br/> **T2** = tensor(int32), tensor(int64)|
Expand Down Expand Up @@ -1237,14 +1239,20 @@ Do not modify directly.*
|BiasSplitGelu|*in* X:**T**<br> *in* bias:**T**<br> *out* Y:**T**|1+|**T** = tensor(float), tensor(float16)|
|ConvTransposeWithDynamicPads|*in* X:**T**<br> *in* W:**T**<br> *in* Pads:**tensor(int64)**<br> *in* B:**T**<br> *out* Y:**T**|1+|**T** = tensor(float), tensor(float16)|
|DequantizeLinear|*in* x:**T1**<br> *in* x_scale:**T2**<br> *in* x_zero_point:**T1**<br> *out* y:**T2**|1+|**T1** = tensor(int32), tensor(int8), tensor(uint8)<br/> **T2** = tensor(float), tensor(float16)|
|DynamicQuantizeMatMul|*in* A:**T1**<br> *in* B:**T2**<br> *in* b_scale:**T1**<br> *in* b_zero_point:**T2**<br> *in* bias:**T1**<br> *out* Y:**T1**|1+|**T1** = tensor(float)<br/> **T2** = tensor(int8), tensor(uint8)|
|EmbedLayerNormalization|*in* input_ids:**T1**<br> *in* segment_ids:**T1**<br> *in* word_embedding:**T**<br> *in* position_embedding:**T**<br> *in* segment_embedding:**T**<br> *in* gamma:**T**<br> *in* beta:**T**<br> *in* mask:**T1**<br> *in* position_ids:**T1**<br> *out* output:**T**<br> *out* mask_index:**T1**<br> *out* embedding_sum:**T**|1+|**T** = tensor(float), tensor(float16)|
|FusedMatMul|*in* A:**T**<br> *in* B:**T**<br> *out* Y:**T**|1+|**T** = tensor(float), tensor(float16)|
|FusedMatMulActivation|*in* A:**T**<br> *in* B:**T**<br> *out* Y:**T**|1+|**T** = tensor(float), tensor(float16)|
|Gelu|*in* X:**T**<br> *out* Y:**T**|1+|**T** = tensor(float), tensor(float16)|
|GroupNorm|*in* X:**T**<br> *in* gamma:**M**<br> *in* beta:**M**<br> *out* Y:**T**|1+|**M** = tensor(float), tensor(float16)<br/> **T** = tensor(float), tensor(float16)|
|MatMulIntegerToFloat|*in* A:**T1**<br> *in* B:**T2**<br> *in* a_scale:**T3**<br> *in* b_scale:**T3**<br> *in* a_zero_point:**T1**<br> *in* b_zero_point:**T2**<br> *in* bias:**T3**<br> *out* Y:**T3**|1+|**T1** = tensor(int8), tensor(uint8)<br/> **T2** = tensor(int8), tensor(uint8)<br/> **T3** = tensor(float), tensor(float16)|
|MultiHeadAttention|*in* query:**T**<br> *in* key:**T**<br> *in* value:**T**<br> *in* bias:**T**<br> *in* key_padding_mask:**M**<br> *in* relative_position_bias:**T**<br> *in* past_key:**T**<br> *in* past_value:**T**<br> *out* output:**T**<br> *out* present_key:**T**<br> *out* present_value:**T**|1+|**M** = tensor(int32)<br/> **T** = tensor(float), tensor(float16)|
|NhwcConv|*in* X:**T**<br> *in* W:**T**<br> *in* B:**T**<br> *out* Y:**T**|1+|**T** = tensor(float), tensor(float16)|
|QAttention|*in* input:**T1**<br> *in* weight:**T2**<br> *in* bias:**T3**<br> *in* input_scale:**T3**<br> *in* weight_scale:**T3**<br> *in* mask_index:**T4**<br> *in* input_zero_point:**T1**<br> *in* weight_zero_point:**T2**<br> *in* past:**T3**<br> *out* output:**T3**<br> *out* present:**T3**|1+|**T1** = tensor(int8), tensor(uint8)<br/> **T2** = tensor(int8), tensor(uint8)<br/> **T3** = tensor(float), tensor(float16)<br/> **T4** = tensor(int32)|
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@fdwr fdwr Dec 8, 2023 •
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Hmm, are these other changes intended? It's supposed to be an update for MatMulIntegerToFloat, but why do I also see QAttention and QLinearConcat?

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Both files need to be updated, kernelDocumentation pipeline stage also verifies these file contents

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@fdwr fdwr Dec 9, 2023 •
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Both files need to be updated

I'm not disputing that we need them, but I am seeking to know why we're seeing these other changes. I'll presume we're seeing them because they are stale after a merge from main and sign off.

(note, if we ever generate this locally and see modifications under other providers, like CUDA, then we should not merge those since we don't build locally with CUDA)

|QLinearAdd|*in* A:**T**<br> *in* A_scale:**tensor(float)**<br> *in* A_zero_point:**T**<br> *in* B:**T**<br> *in* B_scale:**tensor(float)**<br> *in* B_zero_point:**T**<br> *in* C_scale:**tensor(float)**<br> *in* C_zero_point:**T**<br> *out* C:**T**|1+|**T** = tensor(int8), tensor(uint8)|
|QLinearAveragePool|*in* X:**T**<br> *in* x_scale:**tensor(float)**<br> *in* x_zero_point:**T**<br> *in* y_scale:**tensor(float)**<br> *in* y_zero_point:**T**<br> *out* Y:**T**|1+|**T** = tensor(int8), tensor(uint8)|
|QLinearConcat|*in* Y_scale:**TF**<br> *in* Y_zero_point:**T8**<br> *in* inputs:**TV**<br> *out* Y:**T8**|1+|**T8** = tensor(int8), tensor(uint8)<br/> **TF** = tensor(float)<br/> **TV** = tensor(float), tensor(int8), tensor(uint8)|
|QLinearGlobalAveragePool|*in* X:**T**<br> *in* x_scale:**tensor(float)**<br> *in* x_zero_point:**T**<br> *in* y_scale:**tensor(float)**<br> *in* y_zero_point:**T**<br> *out* Y:**T**|1+|**T** = tensor(int8), tensor(uint8)|
|QLinearSigmoid|*in* X:**T**<br> *in* X_scale:**tensor(float)**<br> *in* X_zero_point:**T**<br> *in* Y_scale:**tensor(float)**<br> *in* Y_zero_point:**T**<br> *out* Y:**T**|1+|**T** = tensor(int8), tensor(uint8)|
|QuantizeLinear|*in* x:**T1**<br> *in* y_scale:**T1**<br> *in* y_zero_point:**T2**<br> *out* y:**T2**|1+|**T1** = tensor(float), tensor(float16), tensor(int32)<br/> **T2** = tensor(int8), tensor(uint8)|
|QuickGelu|*in* X:**T**<br> *out* Y:**T**|1+|**T** = tensor(float), tensor(float16)|
Expand All @@ -1263,4 +1271,4 @@ Do not modify directly.*
|DmlFusedMeanVarianceNormalization|*in* input:**T**<br> *out* output:**T**|1+|**T** = tensor(float), tensor(float16)|
|DmlFusedSum|*in* data_0:**T**<br> *out* sum:**T**|1+|**T** = tensor(float), tensor(float16)|
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