From ee0877dbf7ed0d08331ea98c89905bc6299b0001 Mon Sep 17 00:00:00 2001
From: Jens Egholm Pedersen <jens@jepedersen.dk>
Date: Thu, 7 Sep 2023 19:07:45 +0200
Subject: [PATCH] Improved argument parsing for shapes (#51)

---
 nir/ir.py | 23 ++++++++++++++---------
 1 file changed, 14 insertions(+), 9 deletions(-)

diff --git a/nir/ir.py b/nir/ir.py
index 09322fa..d73222c 100644
--- a/nir/ir.py
+++ b/nir/ir.py
@@ -1,5 +1,6 @@
 import typing
 from collections import Counter
+from collections.abc import Sequence
 from dataclasses import dataclass
 
 import numpy as np
@@ -11,6 +12,15 @@
 # Shape is a dict mapping strings to shapes
 Shape = typing.Dict[str, np.ndarray]
 
+def _parse_shape_argument(x: Shape, key: str):
+    if isinstance(x, np.ndarray):
+        return {key: x}
+    elif isinstance(x, Sequence):
+        return {key: np.array(x)}
+    elif isinstance(x, dict):
+        return x
+    else:
+        raise ValueError("Unknown shape argument", x)
 
 @dataclass
 class NIRNode:
@@ -243,11 +253,8 @@ class Flatten(NIRNode):
     end_dim: int = -1  # Last dimension to flatten
 
     def __post_init__(self):
-        assert list(self.input_shape.keys()) == [
-            "input"
-        ], "Flatten must have one input: `input`"
-        if isinstance(self.input_shape, np.ndarray):
-            self.input_shape = {"input": self.input_shape}
+        self.input_shape = _parse_shape_argument(self.input_shape, "input")
+        print(self.input_shape)
         concat = self.input_shape["input"][self.start_dim : self.end_dim].prod()
         self.output_shape = {
             "output": np.array(
@@ -325,8 +332,7 @@ class Input(NIRNode):
     input_shape: Shape
 
     def __post_init__(self):
-        if isinstance(self.input_shape, np.ndarray):
-            self.input_shape = {"input": self.input_shape}
+        self.input_shape = _parse_shape_argument(self.input_shape, "input")
         self.output_shape = {"output": self.input_shape["input"]}
 
 
@@ -431,8 +437,7 @@ class Output(NIRNode):
     output_shape: Shape
 
     def __post_init__(self):
-        if isinstance(self.output_shape, np.ndarray):
-            self.output_shape = {"output": self.output_shape}
+        self.output_shape = _parse_shape_argument(self.output_shape, "output")
         self.input_shape = {"input": self.output_shape["output"]}