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alex-yang-upennalex-yang-upenn
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minor fixes
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3 files changed

+16
-200
lines changed

3 files changed

+16
-200
lines changed

‎hls4ml/backends/vitis_accelerator/supported_boards.json‎

Lines changed: 7 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -2,11 +2,16 @@
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"alveo-u55c": {
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"part": "xcu55c-fsvh2892-2L-e",
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"platform": "xilinx_u55c_gen3x16_xdma_3_202210_1",
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"memory": {"type": "hbm", "channels": 32}
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"memory": {"type": "hbm", "channels": 32, "capacity": 16}
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},
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"alveo-u50": {
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"part": "xcu50-fsvh2104-2-e",
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"platform": "xilinx_u50_gen3x16_xdma_5_202210_1",
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"memory": {"type": "hbm", "channels": 32, "capacity": 8}
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},
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"alveo-u250": {
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"part": "xcu250-figd2104-2L-e",
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"platform": "xilinx_u250_xdma_201830_2",
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"memory": {"type": "ddr", "channels": 4}
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"memory": {"type": "ddr", "channels": 4, "capacity": 64}
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}
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}

‎hls4ml/backends/vitis_accelerator/vitis_accelerator_config.py‎

Lines changed: 1 addition & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -13,8 +13,7 @@ def __init__(self, config):
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if self.board in self.supported_boards.keys():
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board_info = self.supported_boards[self.board]
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self.part = board_info['part']
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if self.board.startswith('alveo'):
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self.platform = board_info['platform']
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self.platform = board_info['platform']
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self.memory_type = board_info['memory']['type']
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self.memory_channel_count = board_info['memory']['channels']
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else:

‎vitis_accelerator_test/9_Vitis_Accel.ipynb‎

Lines changed: 8 additions & 196 deletions
Original file line numberDiff line numberDiff line change
@@ -11,18 +11,9 @@
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"execution_count": null,
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"2024-05-16 06:16:51.322811: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: SSE4.1 SSE4.2 AVX AVX2 FMA\n",
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"To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n"
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]
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}
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],
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"outputs": [],
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"source": [
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"from tensorflow.keras.models import load_model\n",
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"from qkeras.utils import _add_supported_quantized_objects\n",
@@ -44,50 +35,9 @@
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"execution_count": null,
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"2024-05-16 06:16:59.043487: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: SSE4.1 SSE4.2 AVX AVX2 FMA\n",
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"To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"WARNING:tensorflow:From /opt/conda/lib/python3.10/site-packages/tensorflow/python/autograph/pyct/static_analysis/liveness.py:83: Analyzer.lamba_check (from tensorflow.python.autograph.pyct.static_analysis.liveness) is deprecated and will be removed after 2023-09-23.\n",
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"Instructions for updating:\n",
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"Lambda fuctions will be no more assumed to be used in the statement where they are used, or at least in the same block. https://github.com/tensorflow/tensorflow/issues/56089\n"
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"WARNING:tensorflow:From /opt/conda/lib/python3.10/site-packages/tensorflow/python/autograph/pyct/static_analysis/liveness.py:83: Analyzer.lamba_check (from tensorflow.python.autograph.pyct.static_analysis.liveness) is deprecated and will be removed after 2023-09-23.\n",
72-
"Instructions for updating:\n",
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"Lambda fuctions will be no more assumed to be used in the statement where they are used, or at least in the same block. https://github.com/tensorflow/tensorflow/issues/56089\n"
74-
]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"WARNING:tensorflow:No training configuration found in the save file, so the model was *not* compiled. Compile it manually.\n"
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"WARNING:tensorflow:No training configuration found in the save file, so the model was *not* compiled. Compile it manually.\n"
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]
89-
}
90-
],
40+
"outputs": [],
9141
"source": [
9242
"model = load_model('model_3/KERAS_check_best_model.h5', custom_objects=co)"
9343
]
@@ -102,131 +52,9 @@
10252
},
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{
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"cell_type": "code",
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"execution_count": 5,
55+
"execution_count": null,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Interpreting Sequential\n",
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"Topology:\n",
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"Layer name: fc1_input, layer type: InputLayer, input shapes: [[None, 16]], output shape: [None, 16]\n",
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"Layer name: fc1, layer type: QDense, input shapes: [[None, 16]], output shape: [None, 64]\n",
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"Layer name: relu1, layer type: Activation, input shapes: [[None, 64]], output shape: [None, 64]\n",
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"Layer name: fc2, layer type: QDense, input shapes: [[None, 64]], output shape: [None, 32]\n",
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"Layer name: relu2, layer type: Activation, input shapes: [[None, 32]], output shape: [None, 32]\n",
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"Layer name: fc3, layer type: QDense, input shapes: [[None, 32]], output shape: [None, 32]\n",
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"Layer name: relu3, layer type: Activation, input shapes: [[None, 32]], output shape: [None, 32]\n",
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"Layer name: output, layer type: QDense, input shapes: [[None, 32]], output shape: [None, 5]\n",
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"Layer name: softmax, layer type: Softmax, input shapes: [[None, 5]], output shape: [None, 5]\n",
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"-----------------------------------\n",
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"Model\n",
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" Precision: fixed<16,6>\n",
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" ReuseFactor: 1\n",
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" Strategy: Latency\n",
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" BramFactor: 1000000000\n",
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" TraceOutput: False\n",
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"LayerName\n",
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" fc1_input\n",
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" Trace: False\n",
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" Precision\n",
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" result: fixed<16,6>\n",
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" fc1\n",
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" Trace: False\n",
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" Precision\n",
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" result: fixed<16,6>\n",
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" weight: fixed<6,1,TRN,WRAP,0>\n",
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" bias: fixed<6,1,TRN,WRAP,0>\n",
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" fc1_linear\n",
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" Trace: False\n",
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" Precision\n",
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" result: fixed<16,6>\n",
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" relu1\n",
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" Trace: False\n",
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" Precision\n",
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" result: ufixed<6,0,RND_CONV,SAT,0>\n",
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" fc2\n",
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" Trace: False\n",
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" Precision\n",
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" result: fixed<16,6>\n",
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" weight: fixed<6,1,TRN,WRAP,0>\n",
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" bias: fixed<6,1,TRN,WRAP,0>\n",
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" fc2_linear\n",
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" Trace: False\n",
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" Precision\n",
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" result: fixed<16,6>\n",
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" relu2\n",
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" Trace: False\n",
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" Precision\n",
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" result: ufixed<6,0,RND_CONV,SAT,0>\n",
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" fc3\n",
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" Trace: False\n",
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" Precision\n",
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" result: fixed<16,6>\n",
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" weight: fixed<6,1,TRN,WRAP,0>\n",
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" bias: fixed<6,1,TRN,WRAP,0>\n",
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" fc3_linear\n",
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" Trace: False\n",
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" Precision\n",
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" result: fixed<16,6>\n",
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" relu3\n",
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" Trace: False\n",
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" Precision\n",
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" result: ufixed<6,0,RND_CONV,SAT,0>\n",
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" output\n",
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" Trace: False\n",
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" Precision\n",
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" result: fixed<16,6>\n",
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" weight: fixed<6,1,TRN,WRAP,0>\n",
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" bias: fixed<6,1,TRN,WRAP,0>\n",
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" output_linear\n",
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" Trace: False\n",
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" Precision\n",
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" result: fixed<16,6>\n",
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" softmax\n",
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" Trace: False\n",
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" Precision\n",
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" result: fixed<16,6>\n",
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" exp_table_t: ap_fixed<18,8>\n",
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" inv_table_t: ap_fixed<18,4>\n",
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"-----------------------------------\n",
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"Interpreting Sequential\n",
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"Topology:\n",
196-
"Layer name: fc1_input, layer type: InputLayer, input shapes: [[None, 16]], output shape: [None, 16]\n",
197-
"Layer name: fc1, layer type: QDense, input shapes: [[None, 16]], output shape: [None, 64]\n",
198-
"Layer name: relu1, layer type: Activation, input shapes: [[None, 64]], output shape: [None, 64]\n",
199-
"Layer name: fc2, layer type: QDense, input shapes: [[None, 64]], output shape: [None, 32]\n",
200-
"Layer name: relu2, layer type: Activation, input shapes: [[None, 32]], output shape: [None, 32]\n",
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"Layer name: fc3, layer type: QDense, input shapes: [[None, 32]], output shape: [None, 32]\n",
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"Layer name: relu3, layer type: Activation, input shapes: [[None, 32]], output shape: [None, 32]\n",
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"Layer name: output, layer type: QDense, input shapes: [[None, 32]], output shape: [None, 5]\n",
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"Layer name: softmax, layer type: Softmax, input shapes: [[None, 5]], output shape: [None, 5]\n",
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"Creating HLS model\n",
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"Writing HLS project\n",
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"WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n"
208-
]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"WARNING:tensorflow:Compiled the loaded model, but the compiled metrics have yet to be built. `model.compile_metrics` will be empty until you train or evaluate the model.\n"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Done\n",
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"\n",
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"\n",
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"Writing Accelerator code\n",
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"WARNING: You set a Part that does not correspond to the Board you specified.The correct Part is now set.\n",
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"Done\n"
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]
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}
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],
57+
"outputs": [],
23058
"source": [
23159
"import sys\n",
23260
"import os\n",
@@ -271,25 +99,9 @@
27199
},
272100
{
273101
"cell_type": "code",
274-
"execution_count": 6,
102+
"execution_count": null,
275103
"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Part: xcvu13p-flga2577-2-e\n",
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"ClockPeriod: 5\n",
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"IOType: io_parallel\n",
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"HLSConfig\n",
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"AcceleratorConfig\n",
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" Board: alveo-u55c\n",
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" Num_Kernel: 1\n",
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" Num_Thread: 1\n",
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" Batchsize: 8192\n"
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]
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}
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],
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"outputs": [],
293105
"source": [
294106
"plotting.print_dict(hls4ml.backends.get_backend('VitisAccelerator').create_initial_config())"
295107
]

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