title: I used plaidml in python but my GPU did not run. ( I use Macbook Pro 16, 2019)
body: <p>I followed the instructions below:
  <a href="https://plaidml.github.io/plaidml/docs/install#macos" rel="nofollow noreferrer">https://plaidml.github.io/plaidml/docs/install#macos</a></p>
  <p>And run codes starting with</p>
  <pre><code>from os import environ
  environ[&quot;KERAS_BACKEND&quot;] = &quot;plaidml.keras.backend&quot;
  
  
  import keras
  from keras.models import Sequential
  from keras.layers import Dense
  from keras.optimizers import Adam
  </code></pre>
  <p>After setting which GPU to use</p>
  <pre><code>Default Config Devices:
     llvm_cpu.0 : CPU (via LLVM)
     metal_intel(r)_uhd_graphics_630.0 : Intel(R) UHD Graphics 630 (Metal)
     metal_amd_radeon_pro_5300m.0 : AMD Radeon Pro 5300M (Metal)
  
  Experimental Config Devices:
     llvm_cpu.0 : CPU (via LLVM)
     opencl_amd_radeon_pro_5300m_compute_engine.0 : AMD AMD Radeon Pro 5300M Compute Engine (OpenCL)
     metal_intel(r)_uhd_graphics_630.0 : Intel(R) UHD Graphics 630 (Metal)
     opencl_intel_uhd_graphics_630.0 : Intel Inc. Intel(R) UHD Graphics 630 (OpenCL)
     metal_amd_radeon_pro_5300m.0 : AMD Radeon Pro 5300M (Metal)
  
  Using experimental devices can cause poor performance, crashes, and other nastiness.
  
  Enable experimental device support? (y,n)[n]:y
  
  Multiple devices detected (You can override by setting PLAIDML_DEVICE_IDS).
  Please choose a default device:
  
     1 : llvm_cpu.0
     2 : opencl_amd_radeon_pro_5300m_compute_engine.0
     3 : metal_intel(r)_uhd_graphics_630.0
     4 : opencl_intel_uhd_graphics_630.0
     5 : metal_amd_radeon_pro_5300m.0
  
  Default device? (1,2,3,4,5)[1]:2
  
  Selected device:
      opencl_amd_radeon_pro_5300m_compute_engine.0
  
  Almost done. Multiplying some matrices...
  Tile code:
    function (B[X,Z], C[Z,Y]) -&gt; (A) { A[x,y : X,Y] = +(B[x,z] * C[z,y]); }
  Whew. That worked.```
  
  
  I ran the jupyter notebook and codes the shell showed
  
  (plaidml-venv) tom@TomdeMacBook-Pro ~ % jupyter notebook
  [I 00:33:57.459 NotebookApp] [jupyter_nbextensions_configurator] enabled 0.4.1
  [I 00:33:57.460 NotebookApp] Serving notebooks from local directory: /Users/tom
  [I 00:33:57.460 NotebookApp] The Jupyter Notebook is running at:
  ....
  ....
  [I 00:34:14.427 NotebookApp] Kernel started: 85afcfbd-f2a5-4c2a-b5ef-0b5d2bd13c67
  [I 00:34:21.789 NotebookApp] Starting buffering for 85afcfbd-f2a5-4c2a-b5ef-0b5d2bd13c67:2e235bb3866a4a8785f81f761cca51b7
  [I 00:34:22.002 NotebookApp] Kernel restarted: 85afcfbd-f2a5-4c2a-b5ef-0b5d2bd13c67
  [I 00:34:22.461 NotebookApp] Restoring connection for 85afcfbd-f2a5-4c2a-b5ef-0b5d2bd13c67:2e235bb3866a4a8785f81f761cca51b7
  [I 00:34:22.461 NotebookApp] Replaying 3 buffered messages
  2021-05-05 00:34:27.072860: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set
  2021-05-05 00:34:27.073059: I tensorflow/core/platform/cpu_feature_guard.cc:142] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA
  To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
  2021-05-05 00:34:30.750011: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:116] None of the MLIR optimization passes are enabled (registered 2)
  </code></pre>
  <p>My AMD GPU, which I chose as target did not show any activity.</p>
  <p><a href="https://i.stack.imgur.com/zvf1Q.png" rel="nofollow noreferrer">enter image description here</a>
  Could you help me?</p>