Create app.py

app.py

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+import numpy as np
+import tensorflow as tf
+from huggingface_hub import from_pretrained_keras
+
+import gradio as gr
+
+## -- DIGIT ENCODER AND DECODER -- ##
+class CharacterTable:
+    """Given a set of characters:
+    + Encode them to a one-hot integer representation
+    + Decode the one-hot or integer representation to their character output
+    + Decode a vector of probabilities to their character output
+    """
+
+    def __init__(self, chars):
+        """Initialize character table.
+        # Arguments
+            chars: Characters that can appear in the input.
+        """
+        self.chars = sorted(set(chars))
+        self.char_indices = dict((c, i) for i, c in enumerate(self.chars))
+        self.indices_char = dict((i, c) for i, c in enumerate(self.chars))
+
+    def encode(self, C, num_rows):
+        """One-hot encode given string C.
+        # Arguments
+            C: string, to be encoded.
+            num_rows: Number of rows in the returned one-hot encoding. This is
+                used to keep the # of rows for each data the same.
+        """
+        x = np.zeros((num_rows, len(self.chars)))
+        for i, c in enumerate(C):
+            x[i, self.char_indices[c]] = 1
+        return x
+
+    def decode(self, x, calc_argmax=True):
+        """Decode the given vector or 2D array to their character output.
+        # Arguments
+            x: A vector or a 2D array of probabilities or one-hot representations;
+                or a vector of character indices (used with `calc_argmax=False`).
+            calc_argmax: Whether to find the character index with maximum
+                probability, defaults to `True`.
+        """
+        if calc_argmax:
+            x = x.argmax(axis=-1)
+        return "".join(self.indices_char[x] for x in x)
+        
+   
+   
+## -- INFERENCE CODE -- ##
+def check_num_validity(a, b):
+    """Validates the inputs before feeding to the model.
+       Checks if both the inputs are positive integers and are not more than 5 digits.
+    """
+    if a.isdigit() and b.isdigit():
+        if len(a) <= 5 and len(b) <= 5:
+            return True, None
+        else:
+            return False, "Input can contain maximum of five digits"
+    else:
+        return False, "Input has to be positive integers (each can be max 5 digits)"
+
+def add_2_nums(a, b):
+    """Performs the model inference after input validation.
+    """
+    a = a.strip()
+    b = b.strip()
+    
+    ip_val_op = check_num_validity(a, b)
+
+    if ip_val_op[0]:
+        # Input encoding
+        q = f"{a.strip()}+{b.strip()}"
+        query = q + " " * (MAXLEN - len(q))
+        rev_query = query[::-1]
+        
+        inp = ctable.encode(rev_query, MAXLEN)
+        inp = np.expand_dims(inp, axis=0)
+
+        # Prediction and output decoding
+        preds = np.argmax(model.predict(inp), axis=-1)
+        guess = ctable.decode(preds[0], calc_argmax=False)
+
+        return guess, rev_query, query
+    else:
+        return "", "Error", ip_val_op[1]
+   
+   
+## -- LSTM INFERENCE SETUP --##
+# Setup for encoding and decoding the inputs     
+chars = "0123456789+ "
+ctable = CharacterTable(chars)
+DIGITS = 5
+REVERSE = True
+
+# Maximum length of input is 'int + int' (e.g., '345+678'). Maximum length of
+# int is DIGITS.
+MAXLEN = DIGITS + 1 + DIGITS
+
+# Model
+model = from_pretrained_keras("vdprabhu/addition-lstm")
+
+## -- GRADIO SETUP -- ##
+inputs = [gr.Textbox(), gr.Textbox()]
+outputs = [gr.Textbox(label="LSTM Output"), gr.Textbox(label="LSTM Input"), gr.Textbox(label="User Query")]
+
+examples = [[53511,98888], [452,12]] 
+title = "Addition using LSTM"
+
+more_text = "It is interesting to note that the input is reversed before feeding to LSTM. Sequence order inversion introduces shorter term dependencies between source and target for this problem."
+description = f"LSTM model is used to add two numbers, provided as strings.\n\n{more_text}"
+
+article = """
+<p style='text-align: center'>
+    <a href='https://keras.io/examples/nlp/addition_rnn/' target='_blank'>Keras Example by Smerity and others</a>
+    <br>
+    Space by Vrinda Prabhu
+    </p>
+"""
+
+gr.Interface(fn=add_2_nums, inputs=inputs, outputs=outputs,  examples=examples, article=article, allow_flagging="never", analytics_enabled=False,
+  title=title, description=description).launch(enable_queue=True)