New URL for the ETDump page (#5809)

Summary:
Pull Request resolved: #5809

This diff is to rename the "sdk-etdump" documentation page to just "etdump".

Old URL: https://pytorch.org/executorch/main/sdk-etdump.html
New URL ("sdk" is removed):
https://pytorch.org/executorch/main/etdump.html

Design doc: https://docs.google.com/document/d/1l6DYTq9Kq6VrPohruRFP-qScZDj01W_g4zlKyvqKGF4/edit?usp=sharing

Reviewed By: dbort

Differential Revision: D63738952

fbshipit-source-id: dda59dc74512aacd2ad168a36e567556b44baa2f

Author: Olivia-liu

backends/apple/mps/setup.md

@@ -116,7 +116,7 @@ python3 -m examples.apple.mps.scripts.mps_example --model_name="mv3" --no-use_fp
 cd executorch
 python3 -m examples.apple.mps.scripts.mps_example --model_name="mv3" --generate_etrecord -b
 ```
-2. Run your Program on the ExecuTorch runtime and generate an [ETDump](./sdk-etdump.md).
+2. Run your Program on the ExecuTorch runtime and generate an [ETDump](./etdump.md).
 ```
 ./cmake-out/examples/apple/mps/mps_executor_runner --model_path mv3_mps_bundled_fp16.pte --bundled_program --dump-outputs
 ```

docs/source/build-run-coreml.md

@@ -100,15 +100,15 @@ python3 -m examples.apple.coreml.scripts.export --model_name mv3 --generate_etre
 # Builds `coreml_executor_runner`.
 ./examples/apple/coreml/scripts/build_executor_runner.sh
 ```
-3. Run and generate an [ETDump](./sdk-etdump.md).
+3. Run and generate an [ETDump](./etdump.md).
 ```bash
 cd executorch
 
 # Generate the ETDump file.
 ./coreml_executor_runner --model_path mv3_coreml_all.pte --profile_model --etdump_path etdump.etdp
 ```
 
-4. Create an instance of the [Inspector API](./sdk-inspector.rst) by passing in the [ETDump](./sdk-etdump.md) you have sourced from the runtime along with the optionally generated [ETRecord](./etrecord.rst) from step 1 or execute the following command in your terminal to display the profiling data table.
+4. Create an instance of the [Inspector API](./sdk-inspector.rst) by passing in the [ETDump](./etdump.md) you have sourced from the runtime along with the optionally generated [ETRecord](./etrecord.rst) from step 1 or execute the following command in your terminal to display the profiling data table.
 ```bash
 python examples/apple/coreml/scripts/inspector_cli.py --etdump_path etdump.etdp --etrecord_path mv3_coreml.bin
 ```

docs/source/devtools-overview.md

@@ -36,7 +36,7 @@ ETDump (ExecuTorch Dump) is the binary blob that is generated by the runtime aft
 If you only care about looking at the raw performance data without linking back to source code and other extensive features, an ETDump alone will be enough to leverage the basic features of the Developer Tools. For the full experience, it is recommended that the users also generate an ETRecord.
 ```
 
-More details are available in the [ETDump documentation](sdk-etdump.md) on how to generate and store an ETDump from the runtime.
+More details are available in the [ETDump documentation](etdump.md) on how to generate and store an ETDump from the runtime.
 
 
 ### Inspector APIs

docs/source/etdump.md

@@ -0,0 +1,44 @@
+# Prerequisite | ETDump - ExecuTorch Dump
+
+ETDump (ExecuTorch Dump) is one of the core components of the ExecuTorch Developer Tools. It is the mechanism through which all forms of profiling and debugging data is extracted from the runtime. Users can't parse ETDump directly; instead, they should pass it into the Inspector API, which deserializes the data, offering interfaces for flexible analysis and debugging.
+
+
+## Generating an ETDump
+
+Generating an ETDump is a relatively straightforward process. Users can follow the steps detailed below to integrate it into their application that uses ExecuTorch.
+
+1. ***Include*** the ETDump header in your code.
+```C++
+#include <executorch/devtools/etdump/etdump_flatcc.h>
+```
+
+2. ***Create*** an Instance of the ETDumpGen class and pass it into the `load_method` call that is invoked in the runtime.
+
+```C++
+torch::executor::ETDumpGen etdump_gen = torch::executor::ETDumpGen();
+Result<Method> method =
+      program->load_method(method_name, &memory_manager, &etdump_gen);
+```
+
+3. ***Dump Out the ETDump Buffer*** - after the inference iterations have been completed, users can dump out the ETDump buffer. If users are on a device which has a filesystem, they could just write it out to the filesystem. For more constrained embedded devices, users will have to extract the ETDump buffer from the device through a mechanism that best suits them (e.g. UART, JTAG etc.)
+
+```C++
+etdump_result result = etdump_gen.get_etdump_data();
+if (result.buf != nullptr && result.size > 0) {
+    // On a device with a file system users can just write it out
+    // to the file-system.
+    FILE* f = fopen(FLAGS_etdump_path.c_str(), "w+");
+    fwrite((uint8_t*)result.buf, 1, result.size, f);
+    fclose(f);
+    free(result.buf);
+  }
+```
+
+4. ***Compile*** your binary using CMake with the `ET_EVENT_TRACER_ENABLED` pre-processor flag to enable events to be traced and logged into ETDump inside the ExecuTorch runtime. This flag needs to be added to the ExecuTorch library and any operator library that you are compiling into your binary. For reference, you can take a look at `examples/sdk/CMakeLists.txt`. The lines of interest are:
+```
+target_compile_options(executorch INTERFACE -DET_EVENT_TRACER_ENABLED)
+target_compile_options(portable_ops_lib INTERFACE -DET_EVENT_TRACER_ENABLED)
+```
+## Using an ETDump
+
+Pass this ETDump into the [Inspector API](./sdk-inspector.rst) to access this data and do post-run analysis.

docs/source/extension-module.md

@@ -134,7 +134,7 @@ Most of the ExecuTorch APIs, including those described above, return either `Res
 
 ### Profile the Module
 
-Use [ExecuTorch Dump](sdk-etdump.md) to trace model execution. Create an instance of the `ETDumpGen` class and pass it to the `Module` constructor. After executing a method, save the `ETDump` to a file for further analysis. You can capture multiple executions in a single trace if desired.
+Use [ExecuTorch Dump](etdump.md) to trace model execution. Create an instance of the `ETDumpGen` class and pass it to the `Module` constructor. After executing a method, save the `ETDump` to a file for further analysis. You can capture multiple executions in a single trace if desired.
 
 ```cpp
 #include <fstream>

docs/source/index.rst

@@ -203,7 +203,7 @@ Topics in this section will help you get started with ExecuTorch.
    devtools-overview
    bundled-io
    etrecord
-   sdk-etdump
+   etdump
    sdk-profiling
    model-debugging
    sdk-inspector

docs/source/llm/getting-started.md

@@ -774,7 +774,7 @@ Run the export script and the ETRecord will be generated as `etrecord.bin`.
 
 ##### ETDump generation
 
-An ETDump is an artifact generated at runtime containing a trace of the model execution. For more information, see [the ETDump docs](../sdk-etdump.md).
+An ETDump is an artifact generated at runtime containing a trace of the model execution. For more information, see [the ETDump docs](../etdump.md).
 
 Include the ETDump header in your code.
 ```cpp

docs/source/model-debugging.md

@@ -14,7 +14,7 @@ Currently, ExecuTorch supports the following debugging flows:
 For a real example reflecting the steps below, please refer to [example_runner.cpp](https://github.com/pytorch/executorch/blob/main/examples/devtools/example_runner/example_runner.cpp).
 
 1. [Optional] Generate an [ETRecord](./etrecord.rst) while exporting your model. When provided, this enables users to link profiling information back to the eager model source code (with stack traces and module hierarchy).
-2. Integrate [ETDump generation](./sdk-etdump.md) into the runtime and set the debugging level by configuring the `ETDumpGen` object. Then, provide an additional buffer to which intermediate outputs and program outputs will be written. Currently we support two levels of debugging:
+2. Integrate [ETDump generation](./etdump.md) into the runtime and set the debugging level by configuring the `ETDumpGen` object. Then, provide an additional buffer to which intermediate outputs and program outputs will be written. Currently we support two levels of debugging:
     - Program level outputs
     ```C++
     Span<uint8_t> buffer((uint8_t*)debug_buffer, debug_buffer_size);
@@ -30,8 +30,8 @@ For a real example reflecting the steps below, please refer to [example_runner.c
     etdump_gen.set_event_tracer_debug_level(
         EventTracerDebugLogLevel::kIntermediateOutputs);
     ```
-3. Build the runtime with the pre-processor flag that enables tracking of debug events. Instructions are in the [ETDump documentation](./sdk-etdump.md).
-4. Run your model and dump out the ETDump buffer as described [here](./sdk-etdump.md). (Do so similarly for the debug buffer if configured above)
+3. Build the runtime with the pre-processor flag that enables tracking of debug events. Instructions are in the [ETDump documentation](./etdump.md).
+4. Run your model and dump out the ETDump buffer as described [here](./etdump.md). (Do so similarly for the debug buffer if configured above)
 
 
 ### Accessing the debug outputs post run using the Inspector API's

docs/source/sdk-etdump.md

@@ -1,44 +1,3 @@
 # Prerequisite | ETDump - ExecuTorch Dump
 
-ETDump (ExecuTorch Dump) is one of the core components of the ExecuTorch Developer Tools. It is the mechanism through which all forms of profiling and debugging data is extracted from the runtime. Users can't parse ETDump directly; instead, they should pass it into the Inspector API, which deserializes the data, offering interfaces for flexible analysis and debugging.
-
-
-## Generating an ETDump
-
-Generating an ETDump is a relatively straightforward process. Users can follow the steps detailed below to integrate it into their application that uses ExecuTorch.
-
-1. ***Include*** the ETDump header in your code.
-```C++
-#include <executorch/devtools/etdump/etdump_flatcc.h>
-```
-
-2. ***Create*** an Instance of the ETDumpGen class and pass it into the `load_method` call that is invoked in the runtime.
-
-```C++
-torch::executor::ETDumpGen etdump_gen = torch::executor::ETDumpGen();
-Result<Method> method =
-      program->load_method(method_name, &memory_manager, &etdump_gen);
-```
-
-3. ***Dump Out the ETDump Buffer*** - after the inference iterations have been completed, users can dump out the ETDump buffer. If users are on a device which has a filesystem, they could just write it out to the filesystem. For more constrained embedded devices, users will have to extract the ETDump buffer from the device through a mechanism that best suits them (e.g. UART, JTAG etc.)
-
-```C++
-etdump_result result = etdump_gen.get_etdump_data();
-if (result.buf != nullptr && result.size > 0) {
-    // On a device with a file system users can just write it out
-    // to the file-system.
-    FILE* f = fopen(FLAGS_etdump_path.c_str(), "w+");
-    fwrite((uint8_t*)result.buf, 1, result.size, f);
-    fclose(f);
-    free(result.buf);
-  }
-```
-
-4. ***Compile*** your binary using CMake with the `ET_EVENT_TRACER_ENABLED` pre-processor flag to enable events to be traced and logged into ETDump inside the ExecuTorch runtime. This flag needs to be added to the ExecuTorch library and any operator library that you are compiling into your binary. For reference, you can take a look at `examples/sdk/CMakeLists.txt`. The lines of interest are:
-```
-target_compile_options(executorch INTERFACE -DET_EVENT_TRACER_ENABLED)
-target_compile_options(portable_ops_lib INTERFACE -DET_EVENT_TRACER_ENABLED)
-```
-## Using an ETDump
-
-Pass this ETDump into the [Inspector API](./sdk-inspector.rst) to access this data and do post-run analysis.
+Please update your link to <https://pytorch.org/executorch/main/etdump.html>. This URL will be deleted after v0.4.0.

docs/source/sdk-inspector.rst

@@ -6,7 +6,7 @@ Overview
 
 The Inspector APIs provide a convenient interface for analyzing the
 contents of `ETRecord <etrecord.html>`__ and
-`ETDump <sdk-etdump.html>`__, helping developers get insights about model
+`ETDump <etdump.html>`__, helping developers get insights about model
 architecture and performance statistics. It’s built on top of the `EventBlock Class <#eventblock-class>`__ data structure,
 which organizes a group of `Event <#event-class>`__\ s for easy access to details of profiling events.
 

docs/source/sdk-profiling.md

@@ -14,8 +14,8 @@ We provide access to all the profiling data via the Python [Inspector API](./sdk
 ## Steps to Profile a Model in ExecuTorch
 
 1. [Optional] Generate an [ETRecord](./etrecord.rst) while you're exporting your model. If provided this will enable users to link back profiling details to eager model source code (with stack traces and module hierarchy).
-2.  Build the runtime with the pre-processor flags that enable profiling. Detailed in the [ETDump documentation](./sdk-etdump.md).
-3. Run your Program on the ExecuTorch runtime and generate an [ETDump](./sdk-etdump.md).
+2.  Build the runtime with the pre-processor flags that enable profiling. Detailed in the [ETDump documentation](./etdump.md).
+3. Run your Program on the ExecuTorch runtime and generate an [ETDump](./etdump.md).
 4. Create an instance of the [Inspector API](./sdk-inspector.rst) by passing in the ETDump you have sourced from the runtime along with the optionally generated ETRecord from step 1.
     - Through the Inspector API, users can do a wide range of analysis varying from printing out performance details to doing more finer granular calculation on module level.
 

docs/source/tutorials_source/devtools-integration-tutorial.py

@@ -20,7 +20,7 @@
 # This tutorial will show a full end-to-end flow of how to utilize the Developer Tools to profile a model.
 # Specifically, it will:
 #
-# 1. Generate the artifacts consumed by the Developer Tools (`ETRecord <../etrecord.html>`__, `ETDump <../sdk-etdump.html>`__).
+# 1. Generate the artifacts consumed by the Developer Tools (`ETRecord <../etrecord.html>`__, `ETDump <../etdump.html>`__).
 # 2. Create an Inspector class consuming these artifacts.
 # 3. Utilize the Inspector class to analyze the model profiling result.
 
@@ -297,5 +297,5 @@ def forward(self, x):
 #
 # - `ExecuTorch Developer Tools Overview <../devtools-overview.html>`__
 # - `ETRecord <../etrecord.html>`__
-# - `ETDump <../sdk-etdump.html>`__
+# - `ETDump <../etdump.html>`__
 # - `Inspector <../sdk-inspector.html>`__

extension/pybindings/pybindings.pyi

@@ -136,7 +136,7 @@ def _load_for_executorch(
     Args:
         path: File path to the ExecuTorch program as a string.
         enable_etdump: If true, enables an ETDump which can store profiling information.
-            See documentation at https://pytorch.org/executorch/stable/sdk-etdump.html
+            See documentation at https://pytorch.org/executorch/stable/etdump.html
             for how to use it.
         debug_buffer_size: If non-zero, enables a debug buffer which can store
             intermediate results of each instruction in the ExecuTorch program.