Merge branch 'main' into shadertoy-improvements

.github/workflows/ci.yml

@@ -198,9 +198,12 @@ jobs:
           pip install -U -r dev-requirements.txt
           python download-wgpu-native.py
           pip install -e .
-    - name: Test on repo
+    - name: Unit tests
       run: |
           pytest -v tests
+    - name: Memory tests
+      run: |
+          pytest -v tests_mem
 
   # The release builds are done for the platforms that we want to build wheels for.
   # We build wheels, test them, and then upload the wheel as an artifact.

docs/utils.rst

@@ -3,6 +3,45 @@ Utils
 
 The wgpu library provides a few utilities. Note that most functions below need to be explictly imported.
 
+Logger
+------
+
+Errors, warnings, and info messages (including messages generated by
+wgpu-native) are logged using Python's default logging mechanics. The
+wgpu logger instance is in ``wgpu.logger``, but can also be obtained
+via:
+
+.. code-block:: py
+
+    import logging
+    logger = logging.getLogger("wgpu")
+
+
+Diagnostics
+-----------
+
+To print a full diagnostic report:
+
+.. code-block:: py
+
+    wgpu.diagnostics.print_report()
+
+To inspect (for example) the total buffer usage:
+
+.. code-block:: py
+
+    >>> counts = wgpu.diagnostics.object_counts.get_dict()
+    >>> print(counts["Buffer"])
+    {'count': 3, 'resource_mem': 784}
+
+
+.. autoclass:: wgpu._diagnostics.DiagnosticsRoot
+    :members:
+
+
+.. autoclass:: wgpu._diagnostics.Diagnostics
+    :members:
+
 
 Get default device
 ------------------

examples/compute_noop.py

@@ -51,9 +51,9 @@
 # import numpy as np
 #
 # numpy_data = np.frombuffer(data, np.int32)
-# out = compute_with_buffers({0: numpy_data}, {1: numpy_data.nbytes}, compute_shader, n=n)
+# out = compute_with_buffers({0: numpy_data}, {1: numpy_data.nbytes}, shader_source, n=n)
 # result = np.frombuffer(out[1], dtype=np.int32)
-# print(result)
+# print(result.tolist())
 
 
 # %% The long version using the wgpu API