add spam-detection

Signed-off-by: xavier dupré <[email protected]>

Author: sdpython

examples/benchmark/_tools.py

@@ -84,7 +84,7 @@ def convert_model(model_name, output_path, opset=13, verbose=True):
                 '--output', '"%s"' % os.path.abspath(output_path).replace("\\", "/"),
                 '--opset', "%d" % opset]
         if verbose:
-            print("cmd: %s" % " ".join(cmdl))
+            print("cmd: python %s" % " ".join(cmdl))
         pproc = subprocess.Popen(
             cmdl, shell=True, stdin=None, stdout=subprocess.PIPE, stderr=subprocess.PIPE,
             executable=sys.executable.replace("pythonw", "python"))
@@ -139,12 +139,14 @@ def benchmark(url, dest, onnx_name, opset, imgs, verbose=True, threshold=1e-3,
         for a in ort.get_outputs():
             print("  {}: {}, {}".format(a.name, a.type, a.shape))
 
+    # onnxruntime
     input_name = ort.get_inputs()[0].name
     fct_ort = lambda img: ort.run(None, {input_name: img})[0]
     results_ort, duration_ort = measure_time(fct_ort, imgs)
     if verbose:
         print("ORT", len(imgs), duration_ort)
 
+    # tensorflow
     import tensorflow_hub as hub
     from tensorflow import convert_to_tensor
     model = hub.load(url.split("?")[0])
@@ -159,6 +161,7 @@ def benchmark(url, dest, onnx_name, opset, imgs, verbose=True, threshold=1e-3,
         mean_tf = sum(duration_tf) / len(duration_tf)
         print("ratio ORT=%r / TF=%r = %r" % (mean_ort, mean_tf, mean_ort / mean_tf))
 
+    # checks discrepencies
     res = model(imgs_tf[0])
     if isinstance(res, dict):
         if len(res) != 1:

examples/benchmark/tfhub_esrgan.py

@@ -7,7 +7,7 @@
 dest = "tf-esrgan-tf2"
 name = "esrgan-tf2"
 opset = 13
-onnx_name = os.path.join(dest, "esrgan-tf2-%d.onnx" % opset)
+onnx_name = os.path.join(dest, "%s-%d.onnx" % (name, opset))
 
 imgs = generate_random_images()
 

examples/benchmark/tfhub_spam_detection.py

@@ -0,0 +1,15 @@
+# SPDX-License-Identifier: Apache-2.0
+import os
+import random
+import numpy
+from _tools import generate_random_images, measure_time, download_model, convert_model, benchmark
+
+url = "https://tfhub.dev/tensorflow/tutorials/spam-detection/1?tf-hub-format=compressed"
+dest = "tf-spam-detection"
+name = "spam-detection"
+opset = 13
+onnx_name = os.path.join(dest, "%s-%d.onnx" % (name, opset))
+
+imgs = generate_random_images((1, 20), dtype=numpy.int32)
+
+benchmark(url, dest, onnx_name, opset, imgs)

examples/benchmark/tfhub_thunder.py

@@ -7,7 +7,7 @@
 dest = "tf-thunder"
 name = "thunder"
 opset = 13
-onnx_name = os.path.join(dest, "esrgan-tf2-%d.onnx" % opset)
+onnx_name = os.path.join(dest, "%s-%d.onnx" % (name, opset))
 
 imgs = generate_random_images(shape=(1, 256, 256, 3), dtype=numpy.int32)
 

examples/benchmark_tfmodel_ort.py

@@ -8,14 +8,13 @@
 import sys
 import time
 import tarfile
-import zipfile
 import subprocess
 import datetime
 import numpy
 from tqdm import tqdm
 import tensorflow_hub as hub
 import onnxruntime as ort
-from tf2onnx import utils, convert
+from tf2onnx import utils
 
 
 def generate_random_images(shape=(100, 100), n=10):
@@ -80,14 +79,14 @@ def convert_model(model_name, output_path, opset=13, verbose=True):
     """
     if not os.path.exists(output_path):
         begin = datetime.datetime.now()
-        cmd = [sys.executable.replace("pythonw", "python"),
-               '-m', 'tf2onnx.convert', '--saved-model',
-               '"%s"' % model_name.replace("\\", "/"),
-               '--output', '"%s"' % output_path.replace("\\", "/"),
-               '--opset', "%d" % opset]
+        cmdl = ['-m', 'tf2onnx.convert', '--saved-model',
+                '"%s"' % model_name.replace("\\", "/"),
+                '--output', '"%s"' % output_path.replace("\\", "/"),
+                '--opset', "%d" % opset]
         if verbose:
-            print("cmd: %s" % " ".join(cmd))
-        pproc = subprocess.Popen(cmdl, shell=True, stdin=None, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
+            print("cmd: python %s" % " ".join(cmdl))
+        pproc = subprocess.Popen(cmdl, shell=True, stdin=None, stdout=subprocess.PIPE, stderr=subprocess.PIPE,
+                                 executable=sys.executable.replace("pythonw", "python"))
         stdoutdata, stderrdata = pproc.communicate()
         if verbose:
             print('--OUT--')
@@ -99,7 +98,7 @@ def convert_model(model_name, output_path, opset=13, verbose=True):
 
 # Downloads the model
 url = "https://tfhub.dev/captain-pool/esrgan-tf2/1?tf-hub-format=compressed"
-dest = "tf-esrgan-tf2"
+dest = os.path.abspath("tf-esrgan-tf2")
 name = "esrgan-tf2"
 opset = 13
 onnx_name = os.path.join(dest, "esrgan-tf2-%d.onnx" % opset)
@@ -126,4 +125,6 @@ def convert_model(model_name, output_path, opset=13, verbose=True):
 results_tf, duration_tf = measure_time(model, imgs)
 print("TF", len(imgs), duration_tf)
 
-print("ratio ORT / TF", sum(duration_ort) / sum(duration_tf))
+mean_ort = sum(duration_ort) / len(duration_ort)
+mean_tf = sum(duration_tf) / len(duration_tf)
+print("ratio ORT=%r / TF=%r = %r" % (mean_ort, mean_tf, mean_ort / mean_tf))