Update tensorflow_model_support.md

Author: daisyden

docs/tensorflow_model_support.md

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+Tensorflow Model Support in Intel® Low Precision Optimization Tool
+===========================================
+
+Intel® Low Precision Optimization Tool supports diffrent model formats of TensorFlow 1.x and 2.x.
+
+
+| TensorFlow model format | Supported? | Example | Comments |
+| ------ | ------ |------|------|
+| frozen pb | Yes | [examples/tensorflow/image_recognition](examples/tensorflow/image_recognition), [examples/tensorflow/oob_models](examples/tensorflow/oob_models) | |
+| Graph object | Yes | [examples/helloworld/tf1.x](examples/helloworld/tf1.x), [examples/tensorflow/style_transfer](examples/tensorflow/style_transfer), [examples/tensorflow/recommendation/wide_deep_large_ds](examples/tensorflow/recommendation/wide_deep_large_ds) | |
+| GraphDef object | Yes | | |
+| tf1.x checkpoint | Yes | [examples/tensorflow/object_detection](examples/tensorflow/object_detection) | |
+| keras.Model object | Yes | [examples/helloworld/tf2.x](examples/helloworld/tf2.x) | |
+| keras saved model | Yes | [examples/helloworld/tf2.x](examples/helloworld/tf2.x) | |
+| tf2.x saved model | TBD | | |
+| tf2.x h5 format model  | TBD ||
+| slim checkpoint | TBD | |
+| tf1.x saved model | No| | No plan to support it |
+| tf2.x checkpoint | No | | As tf2.x checkpoint only has weight and does not contain any description of the computation, please use different tf2.x model for quantization |
+
+
+# Usage
+
+You can directly pass the directory or object to quantizer, for example:
+```python
+from ilit import Quantization
+quantizer = Quantization('./conf.yaml')
+dataset = mnist_dataset(mnist.test.images, mnist.test.labels)
+data_loader = quantizer.dataloader(dataset=dataset, batch_size=1)
+model = frozen_pb/Graph/GraphDef/checkpoint_path/keras.Model/keras_savedmodel_path
+q_model = quantizer(frozen_pb, q_dataloader=data_loader, eval_func=eval_func)
+
+```
+
+