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[Wait for #2563] [ Mixed ] Create weight with var32 tensor #2566

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This pr create the variable fp32 tensor when we create the Weight and
Optimizer Weight.

. update the manager to create Weight with var32 tensor which
requested to weight pool.
. update the weight requests with Weight Spec and var, grad and var32
tensors which created already.
. add clone Tensor with specific type in tensor.h

Resolves:

Self evaluation:

  1. Build test: [X]Passed [ ]Failed [ ]Skipped
  2. Run test: [X]Passed [ ]Failed [ ]Skipped

Signed-off-by: jijoong.moon [email protected]

We will add Var32 Tensor if the Variable Weight is not Full
precision (FP32). This eables the Weight Update with full precision
and only Apply Gradient Process ueses this Tensor. Therefore, the
lifespan of this tensor should be "ApplyGradient".

. Modify TensorPool to generate Weigth considering Mixed Precsion.

**Self evaluation:**
1. Build test:	 [X]Passed [ ]Failed [ ]Skipped
2. Run test:	 [X]Passed [ ]Failed [ ]Skipped

Signed-off-by: jijoong.moon <[email protected]>
This pr create the variable fp32 tensor when we create the Weight and
Optimizer Weight.

. update the manager to create Weight with  var32 tensor which
requested to weight pool.
. update the weight requests with Weight Spec and var, grad and var32
tensors which created already.
. add clone Tensor with specific type in tensor.h

Resolves:

**Self evaluation:**
1. Build test:	 [X]Passed [ ]Failed [ ]Skipped
2. Run test:	 [X]Passed [ ]Failed [ ]Skipped

Signed-off-by: jijoong.moon <[email protected]>
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taos-ci commented May 7, 2024

📝 TAOS-CI Version: 1.5.20200925. Thank you for submitting PR #2566. Please a submit 1commit/1PR (one commit per one PR) policy to get comments quickly from reviewers. Your PR must pass all verificiation processes of cibot before starting a review process from reviewers. If you are new member to join this project, please read manuals in documentation folder and wiki page. In order to monitor a progress status of your PR in more detail, visit http://ci.nnstreamer.ai/.

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@jijoongmoon, 💯 All CI checkers are successfully verified. Thanks.

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@djeong20 djeong20 left a comment

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Looks good to me except for minor fixes.

@@ -224,7 +224,8 @@ class Manager {
*/
std::vector<Tensor *> requestWeightOptimizerVariables(
const std::vector<TensorDim> &dims, const std::string &name,
const TensorLifespan &lifespan, bool is_grad_clip, bool is_mixed_type,
const std::string &suffix, const TensorLifespan &lifespan,
bool is_grad_clip, bool is_mixed_type,
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this func has incorrect description. might need to update the doc.

Comment on lines +173 to +176
* @brief Get the Weight Gradient tensor object
*
* @param idx Identifier of the weight
* @return Tensor& Reference to the weight grad tensor
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Suggested change
* @brief Get the Weight Gradient tensor object
*
* @param idx Identifier of the weight
* @return Tensor& Reference to the weight grad tensor
* @brief Get the single-precision master weight tensor object
*
* @param idx Identifier of the weight
* @return Tensor& Reference to the master weight tensor

Comment on lines +466 to +469
* @brief Get the Weight Gradient tensor object
*
* @param idx Identifier of the weight
* @return Tensor& Reference to the weight grad tensor
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same here

Suggested change
* @brief Get the Weight Gradient tensor object
*
* @param idx Identifier of the weight
* @return Tensor& Reference to the weight grad tensor
* @brief Get the single-precision master weight tensor object
*
* @param idx Identifier of the weight
* @return Tensor& Reference to the master weight tensor

@@ -114,6 +114,7 @@ class Weight : public Var_Grad {
*
* @param v Already created variable object
* @param g Already created gradient object
* @param v32 Already created gradient object
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Suggested change
* @param v32 Already created gradient object
* @param Already created variable32 object

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@skykongkong8 skykongkong8 left a comment

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LGTM

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@DonghakPark DonghakPark left a comment

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LGTM!

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closed by #2663

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5 participants