Merge pull request #2 from dantp-ai/solution/task-0-1

Solution/task 0 1

minitorch/operators.py

@@ -37,13 +37,13 @@ def neg(x: float) -> float:
 def lt(x: float, y: float) -> float:
     "$f(x) =$ 1.0 if x is less than y else 0.0"
     # TODO: Implement for Task 0.1.
-    raise NotImplementedError('Need to implement for Task 0.1')
+    return float(x < y)
 
 
 def eq(x: float, y: float) -> float:
     "$f(x) =$ 1.0 if x is equal to y else 0.0"
     # TODO: Implement for Task 0.1.
-    raise NotImplementedError('Need to implement for Task 0.1')
+    return float(x == y)
 
 
 def max(x: float, y: float) -> float:
@@ -74,7 +74,7 @@ def sigmoid(x: float) -> float:
     for stability.
     """
     # TODO: Implement for Task 0.1.
-    raise NotImplementedError('Need to implement for Task 0.1')
+    raise NotImplementedError("Need to implement for Task 0.1")
 
 
 def relu(x: float) -> float:
@@ -84,7 +84,7 @@ def relu(x: float) -> float:
     (See https://en.wikipedia.org/wiki/Rectifier_(neural_networks) .)
     """
     # TODO: Implement for Task 0.1.
-    raise NotImplementedError('Need to implement for Task 0.1')
+    return x if x > 0.0 else 0
 
 
 EPS = 1e-6
@@ -103,26 +103,26 @@ def exp(x: float) -> float:
 def log_back(x: float, d: float) -> float:
     r"If $f = log$ as above, compute $d \times f'(x)$"
     # TODO: Implement for Task 0.1.
-    raise NotImplementedError('Need to implement for Task 0.1')
+    raise NotImplementedError("Need to implement for Task 0.1")
 
 
 def inv(x: float) -> float:
     "$f(x) = 1/x$"
     # TODO: Implement for Task 0.1.
-    if x != 0.:
+    if x != 0.0:
         return 1 / x
 
 
 def inv_back(x: float, d: float) -> float:
     r"If $f(x) = 1/x$ compute $d \times f'(x)$"
     # TODO: Implement for Task 0.1.
-    raise NotImplementedError('Need to implement for Task 0.1')
+    raise NotImplementedError("Need to implement for Task 0.1")
 
 
 def relu_back(x: float, d: float) -> float:
     r"If $f = relu$ compute $d \times f'(x)$"
     # TODO: Implement for Task 0.1.
-    raise NotImplementedError('Need to implement for Task 0.1')
+    return d * (x > 0.0)
 
 
 # ## Task 0.3
@@ -144,13 +144,13 @@ def map(fn: Callable[[float], float]) -> Callable[[Iterable[float]], Iterable[fl
          new list
     """
     # TODO: Implement for Task 0.3.
-    raise NotImplementedError('Need to implement for Task 0.3')
+    raise NotImplementedError("Need to implement for Task 0.3")
 
 
 def negList(ls: Iterable[float]) -> Iterable[float]:
     "Use `map` and `neg` to negate each element in `ls`"
     # TODO: Implement for Task 0.3.
-    raise NotImplementedError('Need to implement for Task 0.3')
+    raise NotImplementedError("Need to implement for Task 0.3")
 
 
 def zipWith(
@@ -170,13 +170,13 @@ def zipWith(
 
     """
     # TODO: Implement for Task 0.3.
-    raise NotImplementedError('Need to implement for Task 0.3')
+    raise NotImplementedError("Need to implement for Task 0.3")
 
 
 def addLists(ls1: Iterable[float], ls2: Iterable[float]) -> Iterable[float]:
     "Add the elements of `ls1` and `ls2` using `zipWith` and `add`"
     # TODO: Implement for Task 0.3.
-    raise NotImplementedError('Need to implement for Task 0.3')
+    raise NotImplementedError("Need to implement for Task 0.3")
 
 
 def reduce(
@@ -195,16 +195,16 @@ def reduce(
          fn(x_1, x_0)))`
     """
     # TODO: Implement for Task 0.3.
-    raise NotImplementedError('Need to implement for Task 0.3')
+    raise NotImplementedError("Need to implement for Task 0.3")
 
 
 def sum(ls: Iterable[float]) -> float:
     "Sum up a list using `reduce` and `add`."
     # TODO: Implement for Task 0.3.
-    raise NotImplementedError('Need to implement for Task 0.3')
+    raise NotImplementedError("Need to implement for Task 0.3")
 
 
 def prod(ls: Iterable[float]) -> float:
     "Product of a list using `reduce` and `mul`."
     # TODO: Implement for Task 0.3.
-    raise NotImplementedError('Need to implement for Task 0.3')
+    raise NotImplementedError("Need to implement for Task 0.3")