# Upload numpy array on pynq dram
**URL:** https://discuss.pynq.io/t/upload-numpy-array-on-pynq-dram/5257
**Category:** Support
**Created:** [February 23, 2023, 1:02pm UTC](https://discuss.pynq.io/t/upload-numpy-array-on-pynq-dram/5257 "2023-02-23T13:02:54Z")
**Posts on this page:** 4
**Page:** 1
### Author:  [@fkj1196](https://discuss.pynq.io/u/fkj1196)
#### Post date: [February 23, 2023, 1:02pm UTC](https://discuss.pynq.io/t/upload-numpy-array-on-pynq-dram/5257/1 "2023-02-23T13:02:54Z")
- board : pynq z1
I have a file “input.npy” which have size of 100x100, and type of np.float32.
this file can be uploaded on dram using buffer write like below.
```auto
input_file = np.load('input.npy')
input_dram = allocate(shape=(100, 100), dtype=np.float32)
for i in range(100):
for j in range(100):
input_dram[i][j] = input_file[i][j]
```
However, this way takes a lot of time if data size gets bigger.
I must use attribute “physical\_address” in pynq.buffer.
These two ways delete “physical\_address” of “input\_dram” when executed.
```auto
# way 1
input_dram = allocate(shape=(100, 100), dtype=np.float32)
input_dram = np.load('input.npy')
```
```auto
# way 2
input_file = np.load('input.npy')
input_dram = allocate(shape=(100, 100), dtype=np.float32)
input_dram = input_file.copy()
```
When printing physical address, the error message said AttributeError: ‘numpy.ndarray’ object has no attribute ‘physical\_address’
Is there another way directly upload numpy file on pynq dram?
---
### Author:  [@marioruiz](https://discuss.pynq.io/u/marioruiz)
#### Post date: [February 23, 2023, 1:44pm UTC](https://discuss.pynq.io/t/upload-numpy-array-on-pynq-dram/5257/2 "2023-02-23T13:44:35Z")
Hi @fkj1196,
It takes a lot of time because you are coping element by element.
Code snipped below will overwrite the whole `input_dram` array, so avoid doing this (this is why you get the attribute error)
```python
input_dram = input_file.copy()
```
You can simply do:
```python
input_dram[:] = input_file
```
This will copy your `input_file` object contents to the allocated array.
Mario
---
### Author:  [@fkj1196](https://discuss.pynq.io/u/fkj1196)
#### Post date: [February 23, 2023, 1:57pm UTC](https://discuss.pynq.io/t/upload-numpy-array-on-pynq-dram/5257/3 "2023-02-23T13:57:57Z")
This works very fast.
Appreciate for your answer.
---
### Author:  [@marioruiz](https://discuss.pynq.io/u/marioruiz)
#### Post date: [February 23, 2023, 2:09pm UTC](https://discuss.pynq.io/t/upload-numpy-array-on-pynq-dram/5257/4 "2023-02-23T14:09:09Z")