fix: update tf backend matmul to be compatible with tf.function

ivy/functional/backends/tensorflow/linear_algebra.py

@@ -233,37 +233,24 @@ def matmul(
         x1 = tf.cast(x1, dtype_from)
         x2 = tf.cast(x2, dtype_from)
 
-    if (
-        x1.shape == ()
-        or x2.shape == ()
-        or (len(x1.shape) == len(x2.shape) == 1 and x1.shape != x2.shape)
-        or (len(x1.shape) == len(x2.shape) == 1 and x1.shape != x2.shape)
-        or (len(x1.shape) == 1 and len(x2.shape) >= 2 and x1.shape[0] != x2.shape[-2])
-        or (len(x2.shape) == 1 and len(x1.shape) >= 2 and x2.shape[0] != x1.shape[-1])
-        or (len(x1.shape) >= 2 and len(x2.shape) >= 2 and x1.shape[-1] != x2.shape[-2])
-    ):
-        raise ivy.utils.exceptions.IvyException("Error,shapes not compatible")
-
     x1_padded = False
     x1_padded_2 = False
     x2_padded = False
 
-    if len(x1.shape) == len(x2.shape) == 1:
-        if x1.shape == 0:
+    if tf.reduce_all([tf.equal(tf.rank(x1), tf.rank(x2)), tf.equal(tf.rank(x1), 1)]):
+        if tf.equal(tf.size(x1), 0):
             ret = tf.constant(0)
         else:
             ret = tf.reduce_sum(tf.math.multiply(x1, x2))
-        ret = tf.cast(ret, dtype=dtype_from)  # return ret
-
+        ret = tf.cast(ret, dtype=dtype_from)
     else:
-        if len(x1.shape) == 1:
-            if len(x2.shape) == 2:
+        if tf.equal(tf.rank(x1), 1):
+            if tf.equal(tf.rank(x2), 2):
                 x1_padded_2 = True
-            elif len(x2.shape) > 2:
+            elif tf.greater(tf.rank(x2), 2):
                 x1_padded = True
             x1 = tf.expand_dims(x1, axis=0)
-
-        elif len(x2.shape) == 1 and len(x1.shape) >= 2:
+        elif tf.reduce_all([tf.equal(tf.rank(x2), 1), tf.greater_equal(tf.rank(x1), 2)]):
             x2 = tf.expand_dims(x2, axis=1)
             x2_padded = True
         ret = tf.matmul(x1, x2)