add document for GenAI by LittleLittleCloud · Pull Request #7170 · dotnet/machinelearning

LittleLittleCloud · 2024-06-06T19:07:58Z

We are excited to review your PR.

So we can do the best job, please check:

There's a descriptive title that will make sense to other developers some time from now.
There's associated issues. All PR's should have issue(s) associated - unless a trivial self-evident change such as fixing a typo. You can use the format Fixes #nnnn in your description to cause GitHub to automatically close the issue(s) when your PR is merged.
Your change description explains what the change does, why you chose your approach, and anything else that reviewers should know.
You have included any necessary tests in the same PR.
[ ]
Add desgin document for Add GenAI packages #7169

luisquintanilla · 2024-06-11T20:19:33Z

@NiklasGustafsson @stephentoub @SteveSandersonMS can you please take a look and provide feedback.

This is the design document for the GenAI library which consolidates the models ported to TorchSharp (Phi, Llama, StableDiffusion) into a single library for easier consumption.

stephentoub · 2024-06-11T20:23:06Z

+{
+ public virtual (
+ Tensor, // output token ids [batch_size, sequence_length]
+ Tensor // output logits [batch_size, sequence_length, vocab_size]


Is this the TorchSharp tensor type? Can / should it become the System.Numerics.Tensors one?

Is this the TorchSharp tensor type
Yes
should it become the System.Numerics.Tensors one?
If System.Numerics.Tensors can work with libtorch, then maybe yes.

We're some ways from having Tensor integrated with TorchSharp, it is still experimental and subject to change.

And it would be the TorchSharp shim implementing ITensor, not Tensor from SNT.

Presumably it would be ITensor<T> such that a Tensor<T> could be passed in? The implementation could type test if it were a TorchSharp implementation and act accordingly, presumably.

Yes, in the fullness of time.

stephentoub · 2024-06-11T20:23:59Z

+ where TTokenizer : ITokenizer
+ where TCausalLM : nn.Module<CausalLanguageModelInput, CausalLanguageModelOutput>
+{
+ public CausalLMPipeline<LLama2Tokenizer, Phi3ForCasualLM> Create(LLama2Tokenizer tokenizer, Phi3ForCasualLM model);


Presumably this is intended to instead be a static method on the base class?

Hmmm on the second thought, maybe not. Because CasualLMPipeline and CasualLMPipeline<TTokenizer, TCasualLM> will live in GenAI.Core while Phi3ForCasualLM lives in GenAI.Phi3.
In that case, this Create method is no longer necessary exist, using a constructor to take TTokenzier and TCausalLM would be easier to understand

luisquintanilla

LGTM

LittleLittleCloud · 2024-06-06T19:07:58Z

We are excited to review your PR.

So we can do the best job, please check:

There's a descriptive title that will make sense to other developers some time from now.
There's associated issues. All PR's should have issue(s) associated - unless a trivial self-evident change such as fixing a typo. You can use the format Fixes #nnnn in your description to cause GitHub to automatically close the issue(s) when your PR is merged.
Your change description explains what the change does, why you chose your approach, and anything else that reviewers should know.
You have included any necessary tests in the same PR.
[ ]
Add desgin document for Add GenAI packages #7169

luisquintanilla · 2024-06-11T20:19:33Z

@NiklasGustafsson @stephentoub @SteveSandersonMS can you please take a look and provide feedback.

This is the design document for the GenAI library which consolidates the models ported to TorchSharp (Phi, Llama, StableDiffusion) into a single library for easier consumption.

stephentoub · 2024-06-11T20:23:06Z

+{
+ public virtual (
+ Tensor, // output token ids [batch_size, sequence_length]
+ Tensor // output logits [batch_size, sequence_length, vocab_size]


Is this the TorchSharp tensor type? Can / should it become the System.Numerics.Tensors one?

Is this the TorchSharp tensor type
Yes
should it become the System.Numerics.Tensors one?
If System.Numerics.Tensors can work with libtorch, then maybe yes.

We're some ways from having Tensor integrated with TorchSharp, it is still experimental and subject to change.

And it would be the TorchSharp shim implementing ITensor, not Tensor from SNT.

Presumably it would be ITensor<T> such that a Tensor<T> could be passed in? The implementation could type test if it were a TorchSharp implementation and act accordingly, presumably.

Yes, in the fullness of time.

stephentoub · 2024-06-11T20:23:59Z

+ where TTokenizer : ITokenizer
+ where TCausalLM : nn.Module<CausalLanguageModelInput, CausalLanguageModelOutput>
+{
+ public CausalLMPipeline<LLama2Tokenizer, Phi3ForCasualLM> Create(LLama2Tokenizer tokenizer, Phi3ForCasualLM model);


Presumably this is intended to instead be a static method on the base class?

Hmmm on the second thought, maybe not. Because CasualLMPipeline and CasualLMPipeline<TTokenizer, TCasualLM> will live in GenAI.Core while Phi3ForCasualLM lives in GenAI.Phi3.
In that case, this Create method is no longer necessary exist, using a constructor to take TTokenzier and TCausalLM would be easier to understand

luisquintanilla

LGTM

LittleLittleCloud · 2024-06-06T19:07:58Z

We are excited to review your PR.

So we can do the best job, please check:

There's a descriptive title that will make sense to other developers some time from now.
There's associated issues. All PR's should have issue(s) associated - unless a trivial self-evident change such as fixing a typo. You can use the format Fixes #nnnn in your description to cause GitHub to automatically close the issue(s) when your PR is merged.
Your change description explains what the change does, why you chose your approach, and anything else that reviewers should know.
You have included any necessary tests in the same PR.
[ ]
Add desgin document for Add GenAI packages #7169

luisquintanilla · 2024-06-11T20:19:33Z

@NiklasGustafsson @stephentoub @SteveSandersonMS can you please take a look and provide feedback.

This is the design document for the GenAI library which consolidates the models ported to TorchSharp (Phi, Llama, StableDiffusion) into a single library for easier consumption.

stephentoub · 2024-06-11T20:23:06Z

+{
+ public virtual (
+ Tensor, // output token ids [batch_size, sequence_length]
+ Tensor // output logits [batch_size, sequence_length, vocab_size]


Is this the TorchSharp tensor type? Can / should it become the System.Numerics.Tensors one?

Is this the TorchSharp tensor type
Yes
should it become the System.Numerics.Tensors one?
If System.Numerics.Tensors can work with libtorch, then maybe yes.

We're some ways from having Tensor integrated with TorchSharp, it is still experimental and subject to change.

And it would be the TorchSharp shim implementing ITensor, not Tensor from SNT.

Presumably it would be ITensor<T> such that a Tensor<T> could be passed in? The implementation could type test if it were a TorchSharp implementation and act accordingly, presumably.

Yes, in the fullness of time.

stephentoub · 2024-06-11T20:23:59Z

+ where TTokenizer : ITokenizer
+ where TCausalLM : nn.Module<CausalLanguageModelInput, CausalLanguageModelOutput>
+{
+ public CausalLMPipeline<LLama2Tokenizer, Phi3ForCasualLM> Create(LLama2Tokenizer tokenizer, Phi3ForCasualLM model);


Presumably this is intended to instead be a static method on the base class?

Hmmm on the second thought, maybe not. Because CasualLMPipeline and CasualLMPipeline<TTokenizer, TCasualLM> will live in GenAI.Core while Phi3ForCasualLM lives in GenAI.Phi3.
In that case, this Create method is no longer necessary exist, using a constructor to take TTokenzier and TCausalLM would be easier to understand

luisquintanilla

LGTM

LittleLittleCloud · 2024-06-06T19:07:58Z

We are excited to review your PR.

So we can do the best job, please check:

There's a descriptive title that will make sense to other developers some time from now.
There's associated issues. All PR's should have issue(s) associated - unless a trivial self-evident change such as fixing a typo. You can use the format Fixes #nnnn in your description to cause GitHub to automatically close the issue(s) when your PR is merged.
Your change description explains what the change does, why you chose your approach, and anything else that reviewers should know.
You have included any necessary tests in the same PR.
[ ]
Add desgin document for Add GenAI packages #7169

luisquintanilla · 2024-06-11T20:19:33Z

@NiklasGustafsson @stephentoub @SteveSandersonMS can you please take a look and provide feedback.

This is the design document for the GenAI library which consolidates the models ported to TorchSharp (Phi, Llama, StableDiffusion) into a single library for easier consumption.

stephentoub · 2024-06-11T20:23:06Z

+{
+ public virtual (
+ Tensor, // output token ids [batch_size, sequence_length]
+ Tensor // output logits [batch_size, sequence_length, vocab_size]


Is this the TorchSharp tensor type? Can / should it become the System.Numerics.Tensors one?

Is this the TorchSharp tensor type
Yes
should it become the System.Numerics.Tensors one?
If System.Numerics.Tensors can work with libtorch, then maybe yes.

We're some ways from having Tensor integrated with TorchSharp, it is still experimental and subject to change.

And it would be the TorchSharp shim implementing ITensor, not Tensor from SNT.

Presumably it would be ITensor<T> such that a Tensor<T> could be passed in? The implementation could type test if it were a TorchSharp implementation and act accordingly, presumably.

Yes, in the fullness of time.

stephentoub · 2024-06-11T20:23:59Z

+ where TTokenizer : ITokenizer
+ where TCausalLM : nn.Module<CausalLanguageModelInput, CausalLanguageModelOutput>
+{
+ public CausalLMPipeline<LLama2Tokenizer, Phi3ForCasualLM> Create(LLama2Tokenizer tokenizer, Phi3ForCasualLM model);


Presumably this is intended to instead be a static method on the base class?

Hmmm on the second thought, maybe not. Because CasualLMPipeline and CasualLMPipeline<TTokenizer, TCasualLM> will live in GenAI.Core while Phi3ForCasualLM lives in GenAI.Phi3.
In that case, this Create method is no longer necessary exist, using a constructor to take TTokenzier and TCausalLM would be easier to understand

luisquintanilla

LGTM

LittleLittleCloud · 2024-06-06T19:07:58Z

We are excited to review your PR.

So we can do the best job, please check:

There's a descriptive title that will make sense to other developers some time from now.
There's associated issues. All PR's should have issue(s) associated - unless a trivial self-evident change such as fixing a typo. You can use the format Fixes #nnnn in your description to cause GitHub to automatically close the issue(s) when your PR is merged.
Your change description explains what the change does, why you chose your approach, and anything else that reviewers should know.
You have included any necessary tests in the same PR.
[ ]
Add desgin document for Add GenAI packages #7169

luisquintanilla · 2024-06-11T20:19:33Z

@NiklasGustafsson @stephentoub @SteveSandersonMS can you please take a look and provide feedback.

This is the design document for the GenAI library which consolidates the models ported to TorchSharp (Phi, Llama, StableDiffusion) into a single library for easier consumption.

stephentoub · 2024-06-11T20:23:06Z

+{
+ public virtual (
+ Tensor, // output token ids [batch_size, sequence_length]
+ Tensor // output logits [batch_size, sequence_length, vocab_size]


Is this the TorchSharp tensor type? Can / should it become the System.Numerics.Tensors one?

Is this the TorchSharp tensor type
Yes
should it become the System.Numerics.Tensors one?
If System.Numerics.Tensors can work with libtorch, then maybe yes.

We're some ways from having Tensor integrated with TorchSharp, it is still experimental and subject to change.

And it would be the TorchSharp shim implementing ITensor, not Tensor from SNT.

Presumably it would be ITensor<T> such that a Tensor<T> could be passed in? The implementation could type test if it were a TorchSharp implementation and act accordingly, presumably.

Yes, in the fullness of time.

stephentoub · 2024-06-11T20:23:59Z

+ where TTokenizer : ITokenizer
+ where TCausalLM : nn.Module<CausalLanguageModelInput, CausalLanguageModelOutput>
+{
+ public CausalLMPipeline<LLama2Tokenizer, Phi3ForCasualLM> Create(LLama2Tokenizer tokenizer, Phi3ForCasualLM model);


Presumably this is intended to instead be a static method on the base class?

Hmmm on the second thought, maybe not. Because CasualLMPipeline and CasualLMPipeline<TTokenizer, TCasualLM> will live in GenAI.Core while Phi3ForCasualLM lives in GenAI.Phi3.
In that case, this Create method is no longer necessary exist, using a constructor to take TTokenzier and TCausalLM would be easier to understand

luisquintanilla

LGTM

LittleLittleCloud · 2024-06-06T19:07:58Z

We are excited to review your PR.

So we can do the best job, please check:

There's a descriptive title that will make sense to other developers some time from now.
There's associated issues. All PR's should have issue(s) associated - unless a trivial self-evident change such as fixing a typo. You can use the format Fixes #nnnn in your description to cause GitHub to automatically close the issue(s) when your PR is merged.
Your change description explains what the change does, why you chose your approach, and anything else that reviewers should know.
You have included any necessary tests in the same PR.
[ ]
Add desgin document for Add GenAI packages #7169

luisquintanilla · 2024-06-11T20:19:33Z

@NiklasGustafsson @stephentoub @SteveSandersonMS can you please take a look and provide feedback.

This is the design document for the GenAI library which consolidates the models ported to TorchSharp (Phi, Llama, StableDiffusion) into a single library for easier consumption.

stephentoub · 2024-06-11T20:23:06Z

+{
+ public virtual (
+ Tensor, // output token ids [batch_size, sequence_length]
+ Tensor // output logits [batch_size, sequence_length, vocab_size]


Is this the TorchSharp tensor type? Can / should it become the System.Numerics.Tensors one?

Is this the TorchSharp tensor type
Yes
should it become the System.Numerics.Tensors one?
If System.Numerics.Tensors can work with libtorch, then maybe yes.

We're some ways from having Tensor integrated with TorchSharp, it is still experimental and subject to change.

And it would be the TorchSharp shim implementing ITensor, not Tensor from SNT.

Presumably it would be ITensor<T> such that a Tensor<T> could be passed in? The implementation could type test if it were a TorchSharp implementation and act accordingly, presumably.

Yes, in the fullness of time.

stephentoub · 2024-06-11T20:23:59Z

+ where TTokenizer : ITokenizer
+ where TCausalLM : nn.Module<CausalLanguageModelInput, CausalLanguageModelOutput>
+{
+ public CausalLMPipeline<LLama2Tokenizer, Phi3ForCasualLM> Create(LLama2Tokenizer tokenizer, Phi3ForCasualLM model);


Presumably this is intended to instead be a static method on the base class?

Hmmm on the second thought, maybe not. Because CasualLMPipeline and CasualLMPipeline<TTokenizer, TCasualLM> will live in GenAI.Core while Phi3ForCasualLM lives in GenAI.Phi3.
In that case, this Create method is no longer necessary exist, using a constructor to take TTokenzier and TCausalLM would be easier to understand

luisquintanilla

LGTM

LittleLittleCloud · 2024-06-06T19:07:58Z

We are excited to review your PR.

So we can do the best job, please check:

There's a descriptive title that will make sense to other developers some time from now.
There's associated issues. All PR's should have issue(s) associated - unless a trivial self-evident change such as fixing a typo. You can use the format Fixes #nnnn in your description to cause GitHub to automatically close the issue(s) when your PR is merged.
Your change description explains what the change does, why you chose your approach, and anything else that reviewers should know.
You have included any necessary tests in the same PR.
[ ]
Add desgin document for Add GenAI packages #7169

luisquintanilla · 2024-06-11T20:19:33Z

@NiklasGustafsson @stephentoub @SteveSandersonMS can you please take a look and provide feedback.

This is the design document for the GenAI library which consolidates the models ported to TorchSharp (Phi, Llama, StableDiffusion) into a single library for easier consumption.

stephentoub · 2024-06-11T20:23:06Z

+{
+ public virtual (
+ Tensor, // output token ids [batch_size, sequence_length]
+ Tensor // output logits [batch_size, sequence_length, vocab_size]


Is this the TorchSharp tensor type? Can / should it become the System.Numerics.Tensors one?

Is this the TorchSharp tensor type
Yes
should it become the System.Numerics.Tensors one?
If System.Numerics.Tensors can work with libtorch, then maybe yes.

We're some ways from having Tensor integrated with TorchSharp, it is still experimental and subject to change.

And it would be the TorchSharp shim implementing ITensor, not Tensor from SNT.

Presumably it would be ITensor<T> such that a Tensor<T> could be passed in? The implementation could type test if it were a TorchSharp implementation and act accordingly, presumably.

Yes, in the fullness of time.

stephentoub · 2024-06-11T20:23:59Z

+ where TTokenizer : ITokenizer
+ where TCausalLM : nn.Module<CausalLanguageModelInput, CausalLanguageModelOutput>
+{
+ public CausalLMPipeline<LLama2Tokenizer, Phi3ForCasualLM> Create(LLama2Tokenizer tokenizer, Phi3ForCasualLM model);


Presumably this is intended to instead be a static method on the base class?

Hmmm on the second thought, maybe not. Because CasualLMPipeline and CasualLMPipeline<TTokenizer, TCasualLM> will live in GenAI.Core while Phi3ForCasualLM lives in GenAI.Phi3.
In that case, this Create method is no longer necessary exist, using a constructor to take TTokenzier and TCausalLM would be easier to understand

luisquintanilla

LGTM

LittleLittleCloud · 2024-06-06T19:07:58Z

We are excited to review your PR.

So we can do the best job, please check:

There's a descriptive title that will make sense to other developers some time from now.
There's associated issues. All PR's should have issue(s) associated - unless a trivial self-evident change such as fixing a typo. You can use the format Fixes #nnnn in your description to cause GitHub to automatically close the issue(s) when your PR is merged.
Your change description explains what the change does, why you chose your approach, and anything else that reviewers should know.
You have included any necessary tests in the same PR.
[ ]
Add desgin document for Add GenAI packages #7169

luisquintanilla · 2024-06-11T20:19:33Z

@NiklasGustafsson @stephentoub @SteveSandersonMS can you please take a look and provide feedback.

This is the design document for the GenAI library which consolidates the models ported to TorchSharp (Phi, Llama, StableDiffusion) into a single library for easier consumption.

stephentoub · 2024-06-11T20:23:06Z

+{
+ public virtual (
+ Tensor, // output token ids [batch_size, sequence_length]
+ Tensor // output logits [batch_size, sequence_length, vocab_size]


Is this the TorchSharp tensor type? Can / should it become the System.Numerics.Tensors one?

Is this the TorchSharp tensor type
Yes
should it become the System.Numerics.Tensors one?
If System.Numerics.Tensors can work with libtorch, then maybe yes.

We're some ways from having Tensor integrated with TorchSharp, it is still experimental and subject to change.

And it would be the TorchSharp shim implementing ITensor, not Tensor from SNT.

Presumably it would be ITensor<T> such that a Tensor<T> could be passed in? The implementation could type test if it were a TorchSharp implementation and act accordingly, presumably.

Yes, in the fullness of time.

stephentoub · 2024-06-11T20:23:59Z

+ where TTokenizer : ITokenizer
+ where TCausalLM : nn.Module<CausalLanguageModelInput, CausalLanguageModelOutput>
+{
+ public CausalLMPipeline<LLama2Tokenizer, Phi3ForCasualLM> Create(LLama2Tokenizer tokenizer, Phi3ForCasualLM model);


Presumably this is intended to instead be a static method on the base class?

Hmmm on the second thought, maybe not. Because CasualLMPipeline and CasualLMPipeline<TTokenizer, TCasualLM> will live in GenAI.Core while Phi3ForCasualLM lives in GenAI.Phi3.
In that case, this Create method is no longer necessary exist, using a constructor to take TTokenzier and TCausalLM would be easier to understand

luisquintanilla

LGTM

add document for GenAI
71bd522

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LittleLittleCloud mentioned this pull request Jun 6, 2024
Add GenAI packages #7169
Open
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add document for GenAI
71bd522

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LittleLittleCloud mentioned this pull request Jun 6, 2024
Add GenAI packages #7169
Open
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add document for GenAI
71bd522

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Add GenAI packages #7169
Open
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add document for GenAI
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Add GenAI packages #7169
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add document for GenAI
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Add GenAI packages #7169
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add document for GenAI
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Add GenAI packages #7169
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add document for GenAI
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Add GenAI packages #7169
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LittleLittleCloud merged commit 83b4f18 into dotnet:mainJun 13, 2024

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add document for GenAI
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Add GenAI packages #7169
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LittleLittleCloud merged commit 83b4f18 into dotnet:mainJun 13, 2024

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