diff --git a/README.md b/README.md
index f18bcbe..39dfbf4 100644
--- a/README.md
+++ b/README.md
@@ -14,9 +14,6 @@ This project is a faithful PyTorch implementation of [NeRF](http://www.matthewta
 git clone https://github.com/yenchenlin/nerf-pytorch.git
 cd nerf-pytorch
 pip install -r requirements.txt
-cd torchsearchsorted
-pip install .
-cd ../
 ```
 
 <details>
diff --git a/requirements.txt b/requirements.txt
index 3b1b913..09a7167 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,9 +1,9 @@
-torch>=1.4.0
+torch>=1.7.0
 torchvision>=0.2.1
 imageio
 imageio-ffmpeg
 matplotlib
 configargparse
-tensorboard==1.14.0
+tensorboard==1.15.0
 tqdm
 opencv-python
diff --git a/run_nerf_helpers.py b/run_nerf_helpers.py
index ca270e6..0a3423a 100644
--- a/run_nerf_helpers.py
+++ b/run_nerf_helpers.py
@@ -5,7 +5,7 @@ import torch.nn.functional as F
 import numpy as np
 
 # TODO: remove this dependency
-from torchsearchsorted import searchsorted
+#from torchsearchsorted import searchsorted
 
 
 # Misc
@@ -232,7 +232,8 @@ def sample_pdf(bins, weights, N_samples, det=False, pytest=False):
 
     # Invert CDF
     u = u.contiguous()
-    inds = searchsorted(cdf, u, side='right')
+    # inds = searchsorted(cdf, u, side='right')
+    inds = torch.searchsorted(cdf, u, right=True)
     below = torch.max(torch.zeros_like(inds-1), inds-1)
     above = torch.min((cdf.shape[-1]-1) * torch.ones_like(inds), inds)
     inds_g = torch.stack([below, above], -1)  # (batch, N_samples, 2)