NFC: Replace "toco" with "converter" in loggings.
The testing is for both MLIR-based and TOCO based converters. Calling these "toco" is confusing PiperOrigin-RevId: 351158814 Change-Id: If659d97a2b38feee980d9533db83e73b6798e2d1
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@ -37,11 +37,11 @@ def make_report_table(fp, title, reports):
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title: "Title of the zip file this pertains to."
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reports: a list of conversion attempts. (report_args, report_vals) i.e.
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({"shape": [1,2,3], "type": "tf.float32"},
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{"tf": "SUCCESS", "toco": "FAILURE", "toco_log": "Unsupported type.",
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"tf_log": ""})
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{"tf": "SUCCESS", "converter": "FAILURE",
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"converter_log": "Unsupported type.", "tf_log": ""})
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"""
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# sort reports by if TOCO failure and then TF failure (reversed)
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reports.sort(key=lambda x: x[1]["toco"], reverse=False)
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reports.sort(key=lambda x: x[1]["converter"], reverse=False)
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reports.sort(key=lambda x: x[1]["tf"], reverse=True)
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def result_cell(x, row, col):
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"""Produce a cell with the condition string `x`."""
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@ -76,9 +76,10 @@ log.innerHTML = "<pre>" + data[row][col] + "</pre>";
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}
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""")
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fp.write("var data = \n")
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fp.write(json.dumps([[html.escape(x[1]["tf_log"], quote=True),
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html.escape(x[1]["toco_log"], quote=True)]
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for x in reports]))
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logs = json.dumps([[html.escape(x[1]["tf_log"], quote=True),
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html.escape(x[1]["converter_log"], quote=True)
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] for x in reports])
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fp.write(logs)
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fp.write(";</script>\n")
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# Write the main table and use onclick on the items that have log items.
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@ -110,7 +111,7 @@ log.innerHTML = "<pre>" + data[row][col] + "</pre>";
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fp.write(" <td>%s</td>\n" % html.escape(repr(params[p]), quote=True))
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result_cell(vals["tf"], idx, 0)
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result_cell(vals["toco"], idx, 1)
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result_cell(vals["converter"], idx, 1)
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fp.write("</tr>\n")
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fp.write("</table>\n")
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fp.write("</div>\n")
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@ -422,11 +422,11 @@ def make_zip_of_tests(options,
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"""
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np.random.seed(RANDOM_SEED)
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report = {"toco": report_lib.NOTRUN, "tf": report_lib.FAILED}
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report = {"converter": report_lib.NOTRUN, "tf": report_lib.FAILED}
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# Build graph
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report["tf_log"] = ""
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report["toco_log"] = ""
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report["converter_log"] = ""
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tf.reset_default_graph()
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with tf.Graph().as_default():
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@ -446,7 +446,7 @@ def make_zip_of_tests(options,
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ValueError):
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report["tf_log"] += traceback.format_exc()
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return None, report
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report["toco"] = report_lib.FAILED
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report["converter"] = report_lib.FAILED
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report["tf"] = report_lib.SUCCESS
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# Convert graph to toco
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input_tensors = [(input_tensor.name.split(":")[0], input_tensor.shape,
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@ -468,10 +468,10 @@ def make_zip_of_tests(options,
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output_tensors,
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extra_toco_options=extra_toco_options,
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test_params=param_dict_real)
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report["toco"] = (
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report["converter"] = (
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report_lib.SUCCESS
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if tflite_model_binary is not None else report_lib.FAILED)
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report["toco_log"] = toco_log
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report["converter_log"] = toco_log
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if options.save_graphdefs:
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archive.writestr(zip_path_label + ".pbtxt",
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@ -507,7 +507,7 @@ def make_zip_of_tests(options,
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_, report = build_example(label, param_dict, zip_path_label)
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if report["toco"] == report_lib.FAILED:
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if report["converter"] == report_lib.FAILED:
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ignore_error = False
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if not options.known_bugs_are_errors:
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for pattern, bug_number in options.known_bugs.items():
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@ -517,7 +517,7 @@ def make_zip_of_tests(options,
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if not ignore_error:
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toco_errors += 1
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print("-----------------\nconverter error!\n%s\n-----------------\n" %
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report["toco_log"])
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report["converter_log"])
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convert_report.append((param_dict, report))
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@ -541,7 +541,7 @@ def make_zip_of_tests(options,
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tf_success = sum(
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1 for x in convert_report if x[1]["tf"] == report_lib.SUCCESS)
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toco_success = sum(
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1 for x in convert_report if x[1]["toco"] == report_lib.SUCCESS)
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1 for x in convert_report if x[1]["converter"] == report_lib.SUCCESS)
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percent = 0
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if tf_success > 0:
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percent = float(toco_success) / float(tf_success) * 100.
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