Allow Pynq Z2 board to use Pynq Z1 files

README.md

@@ -125,14 +125,14 @@ dummy_out = accel.execute(dummy_in)
 ##  Example Neural Network Accelerators
 | Dataset                                                        | Topology                | Quantization                                               | Supported boards | Supported build flows
 |----------------------------------------------------------------|-------------------------|------------------------------------------------------------|------------------|------------------|
-| <img src="docs/img/cifar-10.png" width="150"/><br/>CIFAR-10     | CNV (VGG-11-like)       | several variants:<br>1/2-bit weights/activations           | Pynq-Z1<br>ZCU104<br>Ultra96<br>U250              | Pynq-Z1<br>ZCU104<br>Ultra96<br>U250 |
-| <img src="docs/img/mnist.jpg" width="150"/><br/><br>MNIST       | 3-layer fully-connected | several variants:<br>1/2-bit weights/activations           | Pynq-Z1<br>ZCU104<br>Ultra96<br>U250              | Pynq-Z1<br>ZCU104<br>Ultra96<br>U250 |
+| <img src="docs/img/cifar-10.png" width="150"/><br/>CIFAR-10     | CNV (VGG-11-like)       | several variants:<br>1/2-bit weights/activations           | Pynq-Z1<br>Pynq-Z2<br>ZCU104<br>Ultra96<br>U250              | Pynq-Z1<br>ZCU104<br>Ultra96<br>U250 |
+| <img src="docs/img/mnist.jpg" width="150"/><br/><br>MNIST       | 3-layer fully-connected | several variants:<br>1/2-bit weights/activations           | Pynq-Z1<br>Pynq-Z2<br>ZCU104<br>Ultra96<br>U250              | Pynq-Z1<br>ZCU104<br>Ultra96<br>U250 |
 | <img src="docs/img/imagenet.jpg" width="150"/><br/><br>ImageNet | MobileNet-v1            | 4-bit weights & activations<br>8-bit first layer weights | Alveo U250       | Alveo U250 |
 | <img src="docs/img/imagenet.jpg" width="150"/><br/><br>ImageNet | ResNet-50            | 1-bit weights 2-bit activations<br>4-bit residuals<br>8-bit first/last layer weights | Alveo U250       | - |
 | <img src="docs/img/radioml.png" width="150"/><br/><br>RadioML 2018 | 1D CNN (VGG10)     |  4-bit weights & activations | ZCU104  | ZCU104 |
-| <img src="docs/img/maskedfacenet.jpg" width="150"/><br/><br>MaskedFace-Net | [BinaryCoP](https://arxiv.org/pdf/2102.03456)<br/>*Contributed by TU Munich+BMW*  | 1-bit weights & activations | Pynq-Z1       | Pynq-Z1 |
-| <img src="docs/img/keyword-spotting.png" width="150"/><br/><br>Google Speech Commands v2 | 3-layer fully-connected  | 3-bit weights & activations | Pynq-Z1       | Pynq-Z1 |
-| <img src="docs/img/unsw-nb15.jpg" width="150"/><br/><br>UNSW-NB15 | 4-layer fully-connected  | 2-bit weights & activations | Pynq-Z1 <br> ZCU104 <br> Ultra96       | Pynq-Z1 <br> ZCU104 <br> Ultra96 |
+| <img src="docs/img/maskedfacenet.jpg" width="150"/><br/><br>MaskedFace-Net | [BinaryCoP](https://arxiv.org/pdf/2102.03456)<br/>*Contributed by TU Munich+BMW*  | 1-bit weights & activations | Pynq-Z1<br>Pynq-Z2       | Pynq-Z1 |
+| <img src="docs/img/keyword-spotting.png" width="150"/><br/><br>Google Speech Commands v2 | 3-layer fully-connected  | 3-bit weights & activations | Pynq-Z1<br>Pynq-Z2       | Pynq-Z1 |
+| <img src="docs/img/unsw-nb15.jpg" width="150"/><br/><br>UNSW-NB15 | 4-layer fully-connected  | 2-bit weights & activations | Pynq-Z1<br>Pynq-Z2<br>ZCU104<br>Ultra96       | Pynq-Z1<br>Pynq-Z2<br>ZCU104<br>Ultra96 |
 
 *Please note that the build flow for ResNet-50 for the Alveo U250 has known issues and we're currently working on resolving them. However, you can still execute the associated notebook, as we provide a pre-built FPGA bitfile generated with an older Vivado (/FINN) version targeting the [xilinx_u250_xdma_201830_2](https://www.xilinx.com/products/boards-and-kits/alveo/package-files-archive/u250-2018-3-1.html) platform.* <br>
 *Furthermore, please note that you can target other boards (such as the Pynq-Z2 or ZCU102) by changing the build script manually, but these accelerators have not been tested.*
@@ -145,7 +145,7 @@ We welcome community contributions to add more examples to this repo!
 
 `finn-examples` provides pre-built FPGA bitfiles for the following boards:
 
-* **Edge:** Pynq-Z1, Ultra96 and ZCU104
+* **Edge:** Pynq-Z1, Pynq-Z2, Ultra96 and ZCU104
 * **Datacenter:** Alveo U250
 
 It's possible to generate Vivado IP for the provided examples to target *any*

finn_examples/models.py

@@ -28,6 +28,7 @@
 
 import pkg_resources as pk
 
+import logging
 import os
 import platform
 import pynq
@@ -180,6 +181,11 @@ def get_edge_or_pcie():
 
 
 def find_bitfile(model_name, target_platform):
+    if target_platform == "Pynq-Z2":
+        # Pynq Z2 board can use Pynq Z1 bitfiles
+        logging.info(f"Requested platform Pynq-Z2 not built, using Pynq-Z1")
+        target_platform = "Pynq-Z1"
+
     bitfile_exts = {"edge": "bit", "pcie": "xclbin"}
     bitfile_ext = bitfile_exts[get_edge_or_pcie()]
     bitfile_name = "%s.%s" % (model_name, bitfile_ext)