1 files changed, 159 insertions, 0 deletions
diff --git a/src/mlia/target/common/reporters.py b/src/mlia/target/common/reporters.py
new file mode 100644
index 0000000..366e154
--- /dev/null
+++ b/src/mlia/target/common/reporters.py
@@ -0,0 +1,159 @@
+# SPDX-FileCopyrightText: Copyright 2023, Arm Limited and/or its affiliates.
+# SPDX-License-Identifier: Apache-2.0
+"""Common reports module."""
+from __future__ import annotations
+
+from dataclasses import dataclass
+
+from mlia.core.data_analysis import Fact
+from mlia.core.reporting import Column
+from mlia.core.reporting import Format
+from mlia.core.reporting import Report
+from mlia.core.reporting import Table
+from mlia.nn.tensorflow.tflite_compat import TFLiteCompatibilityInfo
+
+
+@dataclass
+class ModelIsNotTFLiteCompatible(Fact):
+    """Model could not be converted into TensorFlow Lite format."""
+
+    custom_ops: list[str] | None = None
+    flex_ops: list[str] | None = None
+
+
+@dataclass
+class TFLiteCompatibilityCheckFailed(Fact):
+    """TensorFlow Lite compatibility check failed by unknown reason."""
+
+
+@dataclass
+class ModelHasCustomOperators(Fact):
+    """Model could not be loaded because it contains custom ops."""
+
+
+def report_tflite_compatiblity(compat_info: TFLiteCompatibilityInfo) -> Report:
+    """Generate report for the TensorFlow Lite compatibility information."""
+    if compat_info.conversion_errors:
+        return Table(
+            [
+                Column("#", only_for=["plain_text"]),
+                Column("Operator", alias="operator"),
+                Column(
+                    "Operator location",
+                    alias="operator_location",
+                    fmt=Format(wrap_width=25),
+                ),
+                Column("Error code", alias="error_code"),
+                Column(
+                    "Error message", alias="error_message", fmt=Format(wrap_width=25)
+                ),
+            ],
+            [
+                (
+                    index + 1,
+                    err.operator,
+                    ", ".join(err.location),
+                    err.code.name,
+                    err.message,
+                )
+                for index, err in enumerate(compat_info.conversion_errors)
+            ],
+            name="TensorFlow Lite conversion errors",
+            alias="tensorflow_lite_conversion_errors",
+        )
+
+    return Table(
+        columns=[
+            Column("Reason", alias="reason"),
+            Column(
+                "Exception details",
+                alias="exception_details",
+                fmt=Format(wrap_width=40),
+            ),
+        ],
+        rows=[
+            (
+                "TensorFlow Lite compatibility check failed with exception",
+                str(compat_info.conversion_exception),
+            ),
+        ],
+        name="TensorFlow Lite compatibility errors",
+        alias="tflite_compatibility",
+    )
+
+
+def handle_model_is_not_tflite_compatible_common(  # type: ignore
+    self, data_item: ModelIsNotTFLiteCompatible
+) -> None:
+    """Advice for TensorFlow Lite compatibility."""
+    if data_item.flex_ops:
+        self.add_advice(
+            [
+                "The following operators are not natively "
+                "supported by TensorFlow Lite: "
+                f"{', '.join(data_item.flex_ops)}.",
+                "Using select TensorFlow operators in TensorFlow Lite model "
+                "requires special initialization of TFLiteConverter and "
+                "TensorFlow Lite run-time.",
+                "Please refer to the TensorFlow documentation for more "
+                "details: https://www.tensorflow.org/lite/guide/ops_select",
+                "Note, such models are not supported by the ML Inference Advisor.",
+            ]
+        )
+
+    if data_item.custom_ops:
+        self.add_advice(
+            [
+                "The following operators appear to be custom and not natively "
+                "supported by TensorFlow Lite: "
+                f"{', '.join(data_item.custom_ops)}.",
+                "Using custom operators in TensorFlow Lite model "
+                "requires special initialization of TFLiteConverter and "
+                "TensorFlow Lite run-time.",
+                "Please refer to the TensorFlow documentation for more "
+                "details: https://www.tensorflow.org/lite/guide/ops_custom",
+                "Note, such models are not supported by the ML Inference Advisor.",
+            ]
+        )
+
+    if not data_item.flex_ops and not data_item.custom_ops:
+        self.add_advice(
+            [
+                "Model could not be converted into TensorFlow Lite format.",
+                "Please refer to the table for more details.",
+            ]
+        )
+
+
+def handle_tflite_check_failed_common(  # type: ignore
+    self, _data_item: TFLiteCompatibilityCheckFailed
+) -> None:
+    """Advice for the failed TensorFlow Lite compatibility checks."""
+    self.add_advice(
+        [
+            "Model could not be converted into TensorFlow Lite format.",
+            "Please refer to the table for more details.",
+        ]
+    )
+
+
+def analyze_tflite_compatibility_common(  # type: ignore
+    self, data_item: TFLiteCompatibilityInfo
+) -> None:
+    """Analyze TensorFlow Lite compatibility information."""
+    if data_item.compatible:
+        return
+
+    if data_item.conversion_failed_with_errors:
+        self.add_fact(
+            ModelIsNotTFLiteCompatible(
+                custom_ops=data_item.required_custom_ops,
+                flex_ops=data_item.required_flex_ops,
+            )
+        )
+
+    if data_item.check_failed_with_unknown_error:
+        self.add_fact(TFLiteCompatibilityCheckFailed())
+
+    if data_item.conversion_failed_for_model_with_custom_ops:
+        self.add_fact(ModelHasCustomOperators())