From 71679e570845f8b8cf9dce7f03ab530f59534d47 Mon Sep 17 00:00:00 2001 From: pritesh2000 Date: Fri, 30 Aug 2024 03:36:24 +0530 Subject: [PATCH] fix typos --- 09_pytorch_model_deployment.ipynb | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/09_pytorch_model_deployment.ipynb b/09_pytorch_model_deployment.ipynb index 12bfbbfa..ab8ff295 100644 --- a/09_pytorch_model_deployment.ipynb +++ b/09_pytorch_model_deployment.ipynb @@ -1573,7 +1573,7 @@ "2. Create an empty list to store prediction dictionaries (we want the function to return a list of dictionaries, one for each prediction).\n", "3. Loop through the target input paths (steps 4-14 will happen inside the loop).\n", "4. Create an empty dictionary for each iteration in the loop to store prediction values per sample.\n", - "5. Get the sample path and ground truth class name (we can do this by infering the class from the path).\n", + "5. Get the sample path and ground truth class name (we can do this by inferring the class from the path).\n", "6. Start the prediction timer using Python's [`timeit.default_timer()`](https://docs.python.org/3/library/timeit.html#timeit.default_timer).\n", "7. Open the image using [`PIL.Image.open(path)`](https://pillow.readthedocs.io/en/stable/reference/Image.html#functions).\n", "8. Transform the image so it's capable of being used with the target model as well as add a batch dimension and send the image to the target device.\n", @@ -1611,7 +1611,7 @@ " class_names: List[str], \n", " device: str = \"cuda\" if torch.cuda.is_available() else \"cpu\") -> List[Dict]:\n", " \n", - " # 2. Create an empty list to store prediction dictionaires\n", + " # 2. Create an empty list to store prediction dictionaries\n", " pred_list = []\n", " \n", " # 3. Loop through target paths\n",