Update base for Update on "[ET-VK] Allow specifying multiple storage types/memory layouts for an operator + register group norm operator"

## Changes

* Handle cases where an operator needs to specify a separate storage type / memory layout for each individual output.

## Motivation

Required for the group norm operator.

## Future Work

Currently, the `tag_memory_meta_pass` graph pass assumes that all tensors participating in a computation (aside from weights) will have the same storage type and memory layout. As more operators are being added, there are more exceptions to this rule.

The pass may need an update in the near future to make it possible to specify required storage types and memory layouts on a more granular level.

Differential Revision: [D77038781](https://our.internmc.facebook.com/intern/diff/D77038781/)

[ghstack-poisoned]

Author: SS-JIA

.ci/scripts/benchmark_tooling/README.md

@@ -77,16 +77,16 @@ python3 .ci/scripts/benchmark_tooling/analyze_benchmark_stability.py \
 
 ##### Filtering Options:
 
-- `--device-pools`: Filter by private device pool names (e.g., "samsung-galaxy-s22-5g", "samsung-galaxy-s22plus-5g")
+- `--device-pools`: Filter by device pool names (e.g., "apple_iphone_15_private", "samsung_s22_private")
 - `--backends`: Filter by specific backend names (e.g.,"xnnpack_q8")
-- `--models`: Filter by specific model names (e.g., "mv3", "meta-llama-llama-3.2-1b-instruct-qlora-int4-eo8")
+- `--models`: Filter by specific model names (e.g., "mv3", "meta-llama/Llama-3.2-1B-Instruct-SpinQuant_INT4_EO8")
 
 #### Example Usage
 
 Filter by multiple private device pools and models:
 ```bash
 # This fetches all private table data for models 'llama-3.2-1B' and 'mv3'
-python3 get_benchmark_analysis_data.py \
+python3 .ci/scripts/benchmark_tooling/get_benchmark_analysis_data.py \
   --startTime "2025-06-01T00:00:00" \
   --endTime "2025-06-11T00:00:00" \
   --device-pools 'apple_iphone_15_private' 'samsung_s22_private' \
@@ -97,7 +97,7 @@ Filter by specific device pool and models:
 ```bash
 # This fetches all private iPhone table data for models 'llama-3.2-1B' and 'mv3',
 # and associated public iPhone data
-python3 get_benchmark_analysis_data.py \
+python3 .ci/scripts/benchmark_tooling/get_benchmark_analysis_data.py \
   --startTime "2025-06-01T00:00:00" \
   --endTime "2025-06-11T00:00:00" \
   --device-pools 'apple_iphone_15_private' \
@@ -140,22 +140,6 @@ fetcher.run(
     end_time="2025-06-17T18:00:00"
 )
 
-# Get results in different formats
-# As DataFrames
-df_results = fetcher.to_df()
-
-# Export to Excel
-fetcher.to_excel(output_dir="./results")
-
-# Export to CSV
-fetcher.to_csv(output_dir="./results")
-
-# Export to JSON
-json_path = fetcher.to_json(output_dir="./results")
-
-# Get raw dictionary results
-dict_results = fetcher.to_dict()
-
 # Use the output_data method for flexible output
 results = fetcher.output_data(output_type="excel", output_dir="./results")
 ```