Added examples

Author: antonwolfy

.github/workflows/build-sphinx.yml

@@ -144,7 +144,7 @@ jobs:
         uses: mshick/add-pr-comment@v2.8.1
         with:
           message: |
-            View rendered docs @ https://intelpython.github.io/dpnp/pulls/${{ env.PR_NUM }}/index.html
+            View rendered docs @ https://intelpython.github.io/dpnp/pull/${{ env.PR_NUM }}/index.html
           allow-repeats: false
 
   clean:

doc/index.rst

@@ -18,4 +18,3 @@ Data Parallel Extension for NumPy*
    :caption: Development information
 
    dpnp_backend_api
-   dpctl

doc/quick_start_guide.rst

@@ -127,3 +127,22 @@ by the source, you will need to run a command as below:
 .. code-block:: bash
 
     pytest -s tests
+
+Examples
+========
+
+The examples below demonstrates a simple usage of the Data Parallel Extension for NumPy*
+
+.. literalinclude:: ../examples/example_sum.py
+  :linenos:
+  :language: python
+  :lines: 35-
+  :caption: Calculate sum of an array
+
+.. literalinclude:: ../examples/example_cfd.py
+  :linenos:
+  :language: python
+  :lines: 35-
+  :caption: Compute follows data paradigm
+
+More examples on how to use ``dpnp`` can be found in ``dpnp/examples``.

examples/example1.py

@@ -36,21 +36,13 @@
 """
 
 
-try:
-    import dpnp
-except ImportError:
-    import os
-    import sys
-
-    root_dir = os.path.join(os.path.dirname(__file__), os.pardir)
-    sys.path.append(root_dir)
-
-    import dpnp
-
 import time
 
+import dpctl
 import numpy
 
+import dpnp
+
 
 def run_dgemm(executor, name, size, test_type, repetition):
     x1 = executor.reshape(
@@ -75,15 +67,23 @@ def run_dgemm(executor, name, size, test_type, repetition):
     return (min_time, med_time, max_time), result.item(5)
 
 
+def get_dtypes():
+    _dtypes_list = [numpy.int32, numpy.int64, numpy.float32]
+    device = dpctl.select_default_device()
+    if device.has_aspect_fp64:
+        _dtypes_list.append(numpy.float64)
+    return _dtypes_list
+
+
 if __name__ == "__main__":
     test_repetition = 5
-    for test_type in [numpy.float64, numpy.float32, numpy.int64, numpy.int32]:
+    for test_type in get_dtypes():
         type_name = numpy.dtype(test_type).name
         print(
             f"...Test data type is {test_type}, each test repetitions {test_repetition}"
         )
 
-        for size in [16, 32, 64, 128]:  # , 256, 512, 1024, 2048, 4096]:
+        for size in [16, 32, 64, 128, 256, 512, 1024]:
             times_python, result_python = run_dgemm(
                 numpy, "<NumPy>", size, test_type, test_repetition
             )
@@ -97,6 +97,6 @@ def run_dgemm(executor, name, size, test_type, repetition):
 
             msg = f"type:{type_name}:N:{size:4}"
             msg += f":__NumPy__:{times_python[1]:.3e}:(min:{times_python[0]:.3e}:max:{times_python[2]:.3e})"
-            msg += f":__SYCL__:{times_sycl[1]:.3e}:(min:{times_sycl[0]:.3e}:max:{times_sycl[2]:.3e})"
+            msg += f":__DPNP__:{times_sycl[1]:.3e}:(min:{times_sycl[0]:.3e}:max:{times_sycl[2]:.3e})"
             msg += f":ratio:{times_python[1]/times_sycl[1]:6.2f}:verification:{verification}"
             print(msg)

examples/example10.py

@@ -28,23 +28,16 @@
 """Example 10.
 
 This example shows simple usage of the DPNP
-in combination with dpCtl.
+in combination with dpctl.
 
 """
 
 import time
 
-try:
-    import dpnp
-except ImportError:
-    import os
-    import sys
-
-    sys.path.insert(0, os.path.abspath("."))
-    import dpnp
-
 import numpy
 
+import dpnp
+
 
 def run(executor, size, test_type, repetition):
     x = executor.reshape(
@@ -61,9 +54,17 @@ def run(executor, size, test_type, repetition):
     return numpy.median(times), result
 
 
+def get_dtypes():
+    _dtypes_list = [numpy.int32, numpy.int64, numpy.float32]
+    device = dpctl.select_default_device()
+    if device.has_aspect_fp64:
+        _dtypes_list.append(numpy.float64)
+    return _dtypes_list
+
+
 def example():
     test_repetition = 5
-    for test_type in [numpy.float64, numpy.float32, numpy.int64, numpy.int32]:
+    for test_type in get_dtypes():
         type_name = numpy.dtype(test_type).name
         print(
             f"...Test data type is {type_name}, each test repetitions {test_repetition}"
@@ -80,7 +81,7 @@ def example():
             else:
                 verification = f"({result_dpnp} != {result_numpy})"
 
-            msg = f"type:{type_name}:N:{size:4}:NumPy:{time_numpy:.3e}:SYCL:{time_dpnp:.3e}"
+            msg = f"type:{type_name}:N:{size:4}:NumPy:{time_numpy:.3e}:DPNP:{time_dpnp:.3e}"
             msg += f":ratio:{time_numpy/time_dpnp:6.2f}:verification:{verification}"
             print(msg)
 
@@ -90,7 +91,7 @@ def example():
         import dpctl
 
         with dpctl.device_context("opencl:gpu") as gpu_queue:
-            gpu_queue.get_sycl_device().dump_device_info()
+            gpu_queue.get_sycl_device().print_device_info()
             example()
 
     except ImportError:

examples/example2.py

@@ -36,36 +36,18 @@
 """
 
 
-try:
-    import dpnp
-except ImportError:
-    import os
-    import sys
-
-    root_dir = os.path.join(os.path.dirname(__file__), os.pardir)
-    sys.path.append(root_dir)
-
-    import dpnp
-
 import time
 
 import numpy
 
-common_function_one_input = numpy.sin
-"""
-Fixed third party function
-"""
-
-
-def get_package_specific_input_data_type(input_type, size):
-    return input_type.arange(size)
+import dpnp
 
 
-def run_third_party_function(input, repetition):
+def run_third_party_function(xp, input, repetition):
     times = []
     for _ in range(repetition):
         start_time = time.time()
-        result = common_function_one_input(input)
+        result = xp.sin(input)
         end_time = time.time()
         times.append(end_time - start_time)
 
@@ -75,18 +57,19 @@ def run_third_party_function(input, repetition):
 
 if __name__ == "__main__":
     test_repetition = 5
-    for input_type in [numpy, dpnp]:
-        type_name = input_type.__name__
+    for xp in [numpy, dpnp]:
+        type_name = xp.__name__
         print(
             f"...Test data type is {type_name}, each test repetitions {test_repetition}"
         )
 
-        for size in [2048, 4096, 8192, 16384, 32768, 65536]:
-            input_data = get_package_specific_input_data_type(input_type, size)
+        for size in range(20, 25):
+            size = 2**size
+            input_data = xp.arange(size)
             result_time, result = run_third_party_function(
-                input_data, test_repetition
+                xp, input_data, test_repetition
             )
 
             print(
-                f"type:{type_name}:N:{size:6}:Time:{result_time:.3e}:result:{result:.3e}"
+                f"type:{type_name}:N:{size:6}:Time:{result_time:.3e}:result:{result}"
             )

examples/example6.py

@@ -32,17 +32,7 @@
 dpnp.random.randn
 """
 
-
-try:
-    import dpnp
-except ImportError:
-    import os
-    import sys
-
-    root_dir = os.path.join(os.path.dirname(__file__), os.pardir)
-    sys.path.append(root_dir)
-
-    import dpnp
+import dpnp
 
 if __name__ == "__main__":
     # TODO

examples/example7.py

@@ -25,7 +25,7 @@
 # THE POSSIBILITY OF SUCH DAMAGE.
 # *****************************************************************************
 
-"""Example 1.
+"""Example 7.
 
 This example shows simple usage of the DPNP
 to calculate square matrix multiplication
@@ -35,22 +35,13 @@
 
 """
 
-
-try:
-    import dpnp
-except ImportError:
-    import os
-    import sys
-
-    root_dir = os.path.join(os.path.dirname(__file__), os.pardir)
-    sys.path.append(root_dir)
-
-    import dpnp
-
 import time
 
+import dpctl
 import numpy
 
+import dpnp
+
 
 def run_function(executor, name, size, test_type, repetition):
     x = executor.reshape(
@@ -69,15 +60,23 @@ def run_function(executor, name, size, test_type, repetition):
     return execution_time, result
 
 
+def get_dtypes():
+    _dtypes_list = [numpy.int32, numpy.int64, numpy.float32]
+    device = dpctl.select_default_device()
+    if device.has_aspect_fp64:
+        _dtypes_list.append(numpy.float64)
+    return _dtypes_list
+
+
 if __name__ == "__main__":
     test_repetition = 5
-    for test_type in [numpy.float64, numpy.float32, numpy.int64, numpy.int32]:
+    for test_type in get_dtypes():
         type_name = numpy.dtype(test_type).name
         print(
             f"...Test data type is {test_type}, each test repetitions {test_repetition}"
         )
 
-        for size in [16, 32, 64, 128, 256, 512, 1024, 2048, 4096]:
+        for size in [256, 512, 1024, 2048, 4096, 8192]:
             time_python, result_python = run_function(
                 numpy, "<NumPy>", size, test_type, test_repetition
             )
@@ -90,6 +89,6 @@ def run_function(executor, name, size, test_type, repetition):
             else:
                 verification = f"({result_mkl} != {result_python})"
 
-            msg = f"type:{type_name}:N:{size:4}:NumPy:{time_python:.3e}:SYCL:{time_mkl:.3e}"
+            msg = f"type:{type_name}:N:{size:4}:NumPy:{time_python:.3e}:DPNP:{time_mkl:.3e}"
             msg += f":ratio:{time_python/time_mkl:6.2f}:verification:{verification}"
             print(msg)

examples/example_bs.py

@@ -32,20 +32,10 @@
 
 """
 
-try:
-    import dpnp as np
-except ImportError:
-    import os
-    import sys
-
-    root_dir = os.path.join(os.path.dirname(__file__), os.pardir)
-    sys.path.append(root_dir)
-
-    import dpnp as np
-
+import dpnp as np
 
 SIZE = 2**8
-DTYPE = np.float64
+DTYPE = np.default_float_type()
 
 SEED = 7777777
 PL, PH = 10.0, 50.0

examples/example_cfd.py

@@ -0,0 +1,48 @@
+# cython: language_level=3
+# -*- coding: utf-8 -*-
+# *****************************************************************************
+# Copyright (c) 2023, Intel Corporation
+# All rights reserved.
+#
+# Redistribution and use in source and binary forms, with or without
+# modification, are permitted provided that the following conditions are met:
+# - Redistributions of source code must retain the above copyright notice,
+#   this list of conditions and the following disclaimer.
+# - Redistributions in binary form must reproduce the above copyright notice,
+#   this list of conditions and the following disclaimer in the documentation
+#   and/or other materials provided with the distribution.
+#
+# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
+# ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
+# LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
+# CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
+# SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
+# INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
+# CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
+# ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF
+# THE POSSIBILITY OF SUCH DAMAGE.
+# *****************************************************************************
+
+"""Example CFD.
+
+This example shows how DPNP follows compute follows data paradigm
+
+"""
+
+import dpnp as np
+
+x = np.empty(3)
+try:
+    x = np.asarray([1, 2, 3], device="gpu")
+except Exception:
+    print("GPU device is not available")
+
+print("Array x allocated on the device:", x.device)
+
+y = np.sum(x)
+
+print("Result y is located on the device:", y.device)  # The same device as x
+print("Shape of y is:", y.shape)  # 0-dimensional array
+print("y=", y)  # Expect 6