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yuxizama
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Benoit Chevallier-Mames
Benoit Chevallier-Mames
parent
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3a9c2a1ffa
@@ -1,45 +1,40 @@
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# Debug
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In this section, you will learn how to debug the compilation process easily and find help in the case that you cannot resolve your issue.
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This document provides guidance on debugging the compilation process.
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## Compiler debug and verbose modes
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There are two [configuration](../guides/configure.md) options that you can use to understand what's happening under the hood during the compilation process.
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Two [configuration](../guides/configure.md) options are available to help you understand the compilation process:
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* **compiler\_verbose\_mode** will print the passes applied by the compiler and let you see the transformations done by the compiler. Also, in the case of a crash, it could narrow down the crash location.
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* **compiler\_debug\_mode** is a lot more detailed version of the verbose mode. This is even better for crashes.
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* **compiler\_verbose\_mode**: Prints the compiler passes and shows the transformations applied. It can help identify the crash location if a crash occurs.
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* **compiler\_debug\_mode**: A more detailed version of the verbose mode, providing additional information, particularly useful for diagnosing crashes.
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{% hint style="warning" %}
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These flags might not work as expected in Jupyter notebooks as they output to stderr directly from C++.
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These flags might not work as expected in Jupyter notebooks as they output to `stderr` directly from C++.
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{% endhint %}
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## Debug artifacts
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**Concrete** has an artifact system to simplify the process of debugging issues.
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**Concrete** includes an artifact system that simplifies the debugging process by automatically or manually exporting detailed information during compilation failures.
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### Automatic export.
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In case of compilation failures, artifacts are exported automatically to the `.artifacts` directory under the working directory. Let's intentionally create a compilation failure to show what is exported.
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### Automatic export
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When a compilation fails, artifacts are automatically exported to the `.artifacts` directory in the working directory. Here's an example of what gets exported when a function fails to compile:
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```python
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def f(x):
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return np.sin(x)
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```
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This function fails to compile because **Concrete** does not support floating-point outputs. When you try to compile it, an exception will be raised and the artifacts will be exported automatically. If you go to the `.artifacts` directory under the working directory, you'll see the following files:
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This function fails to compile because **Concrete** does not support floating-point outputs. When you try to compile it, an exception will be raised and the artifacts will be exported automatically. The following files will be generated in the `.artifacts` directory:
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#### environment.txt
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This file contains information about your setup (i.e., your operating system and python version).
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- **`environment.txt`**: Information about your system setup, including the operating system and Python version.
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```
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Linux-5.12.13-arch1-2-x86_64-with-glibc2.29 #1 SMP PREEMPT Fri, 25 Jun 2021 22:56:51 +0000
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Python 3.8.10
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```
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#### requirements.txt
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This file contains information about Python packages and their versions installed on your system.
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- **`requirements.txt`**: The installed Python packages and their versions.
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```
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astroid==2.15.0
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@@ -51,26 +46,20 @@ wrapt==1.15.0
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zipp==3.15.0
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```
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#### function.txt
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This file contains information about the function you tried to compile.
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- **`function.txt`**: The code of the function that failed to compile.
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```
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def f(x):
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return np.sin(x)
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```
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#### parameters.txt
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This file contains information about the encryption status of the parameters of the function you tried to compile.
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- **`parameters.txt`**: Information about the encryption status function's parameters.
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```
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x :: encrypted
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```
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#### 1.initial.graph.txt
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This file contains the textual representation of the initial computation graph right after tracing.
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- **`1.initial.graph.txt`**: The textual representation of the initial computation graph right after tracing.
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```
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%0 = x # EncryptedScalar<uint3>
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@@ -78,9 +67,7 @@ This file contains the textual representation of the initial computation graph r
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return %1
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```
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#### 2.final.graph.txt
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This file contains the textual representation of the final computation graph right before MLIR conversion.
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- **`final.graph.txt`**: The textual representation of the final computation graph right before MLIR conversion.
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```
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%0 = x # EncryptedScalar<uint3>
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@@ -88,9 +75,7 @@ This file contains the textual representation of the final computation graph rig
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return %1
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```
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#### traceback.txt
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This file contains information about the error that was received.
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- **`traceback.txt`**: Details of the error occurred.
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```
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Traceback (most recent call last):
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@@ -113,9 +98,9 @@ RuntimeError: Function you are trying to compile cannot be converted to MLIR
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return %1
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```
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### Manual exports.
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### Manual exports
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Manual exports are mostly used for visualization. They can be very useful for demonstrations. Here is how to perform one:
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Manual exports are mostly used for visualization and demonstrations. Here is how to perform one:
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```python
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from concrete import fhe
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@@ -133,11 +118,9 @@ circuit = f.compile(inputset, artifacts=artifacts)
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artifacts.export()
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```
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If you go to the `/tmp/custom/export/path` directory, you'll see the following files:
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After running the code, you will find the following files under `/tmp/custom/export/path` directory:
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#### 1.initial.graph.txt
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This file contains the textual representation of the initial computation graph right after tracing.
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- **`1.initial.graph.txt`**: The textual representation of the initial computation graph right after tracing.
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```
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%0 = x # EncryptedScalar<uint1>
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@@ -152,9 +135,7 @@ This file contains the textual representation of the initial computation graph r
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return %8
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```
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#### 2.after-fusing.graph.txt
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This file contains the textual representation of the intermediate computation graph after fusing.
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- **`2.after-fusing.graph.txt`**: The textual representation of the intermediate computation graph after fusing.
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```
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%0 = x # EncryptedScalar<uint1>
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@@ -177,9 +158,7 @@ Subgraphs:
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return %6
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```
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#### 3.final.graph.txt
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This file contains the textual representation of the final computation graph right before MLIR conversion.
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- **`3.final.graph.txt`**: The textual representation of the final computation graph right before MLIR conversion.
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```
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%0 = x # EncryptedScalar<uint3> ∈ [0, 7]
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@@ -202,9 +181,7 @@ Subgraphs:
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return %6
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```
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#### mlir.txt
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This file contains information about the MLIR of the function which was compiled using the provided inputset.
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- **`mlir.txt`**: Information about the MLIR of the function which was compiled using the provided input-set.
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```
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module {
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@@ -218,9 +195,7 @@ module {
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}
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```
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#### client\_parameters.json
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This file contains information about the client parameters chosen by **Concrete**.
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- **`client\_parameters.json`**: Information about the client parameters chosen by **Concrete**.
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```
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{
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@@ -300,17 +275,17 @@ You can seek help with your issue by asking a question directly in the [communit
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## Submitting an issue
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If you cannot find a solution in the community forum, or if you have found a bug in the library, you could create an issue in our GitHub repository.
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If you cannot find a solution in the community forum, or if you have found a bug in the library, you could [create an issue](https://github.com/zama-ai/concrete/issues/new/choose) in our GitHub repository.
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In case of a bug, try to:
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For [bug reports](https://github.com/zama-ai/concrete/issues/new?assignees=&labels=bug%2C+triage&projects=&template=bug_report.md), try to:
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* minimize randomness;
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* minimize your function as much as possible while keeping the bug - this will help to fix the bug faster;
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* include your inputset in the issue;
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* include reproduction steps in the issue;
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* include debug artifacts in the issue.
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* Avoid randomness to ensure reproductibility of the bug
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* Minimize your function while keeping the bug to expedite the fix
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* Include your input-set in the issue
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* Provide clear reproduction steps
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* Include debug artifacts in the issue
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In case of a feature request, try to:
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For [feature requests](https://github.com/zama-ai/concrete/issues/new?assignees=&labels=feature&projects=&template=features.md), try to:
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* give a minimal example of the desired behavior;
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* explain your use case.
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* Give a minimal example of the desired behavior
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* Explain your use case
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