hls4ml.backends.fpga package

Submodules

hls4ml.backends.fpga.fpga_backend module

class hls4ml.backends.fpga.fpga_backend.FPGABackend(name)

Bases: hls4ml.backends.backend.Backend

compile(model)

Compile the generated project that can be linked into Python runtime.

Parameters

model (ModelGraph) – Model to compile.

Raises

Exception – If the project failed to compile

Returns

Returns the name of the compiled library.

Return type

string

compute_conv1d_instructions(in_W, in_C, kernel_size=3, stride=1, pad=0)
compute_conv2d_instructions(in_H, in_W, in_C, kernel_size=3, stride=1, pad=0)
classmethod convert_precision_string(precision)
create_layer_class(layer_class)

Wrap the original layer class into the backend-specific layer class.

Backends should extend base layer classes with new attributes and variables as needed. These new classes are then used within the model.

Parameters

layer_class (class) – Base class to extend

get_closest_reuse_factor(valid_rf, chosen_rf)

Returns closest value to chosen_rf. valid_rf is sorted (obtained from get_valid_reuse_factors()) If two numbers are equally close, return the smallest number.

get_layer_mult_size(layer)
get_valid_reuse_factors(n_in, n_out)
get_writer_flow()
product_type(data_T, weight_T)

Helper function to determine which product implementation to use during inference

set_closest_reuse_factor(layer, n_in, n_out, attribute='reuse_factor')
set_target_reuse_factor(layer)
write(model)

Write the generated project to disk.

This function converts the model to C++ and writes the generated files in the output directory specified in the config.

Parameters

model (ModelGraph) – Model to write.

write_hls(model)

hls4ml.backends.fpga.fpga_layers module

class hls4ml.backends.fpga.fpga_layers.BatchNormalizationQuantizedTanh(model, name, attributes, inputs, outputs=None)

Bases: hls4ml.model.layers.Layer

Merged Batch Normalization and quantized (binary or ternary) Tanh layer. The mean, variance, beta, gamma parameters are folded into the threshold(s) at which the sign of the input flips after the quantized (binary or ternary) Tanh activation.

initialize()
set_thresholds(scale, bias, ternary_threshold=0.5)

hls4ml.backends.fpga.fpga_types module

class hls4ml.backends.fpga.fpga_types.ACFixedPrecisionDefinition

Bases: hls4ml.backends.fpga.fpga_types.PrecisionDefinition

definition_cpp()
class hls4ml.backends.fpga.fpga_types.ACIntegerPrecisionDefinition

Bases: hls4ml.backends.fpga.fpga_types.PrecisionDefinition

definition_cpp()
class hls4ml.backends.fpga.fpga_types.ACTypeConverter

Bases: hls4ml.backends.fpga.fpga_types.FixedPrecisionConverter

class hls4ml.backends.fpga.fpga_types.APFixedPrecisionDefinition

Bases: hls4ml.backends.fpga.fpga_types.PrecisionDefinition

definition_cpp()
class hls4ml.backends.fpga.fpga_types.APIntegerPrecisionDefinition

Bases: hls4ml.backends.fpga.fpga_types.PrecisionDefinition

definition_cpp()
class hls4ml.backends.fpga.fpga_types.APTypeConverter

Bases: hls4ml.backends.fpga.fpga_types.FixedPrecisionConverter

class hls4ml.backends.fpga.fpga_types.ArrayVariableConverter(type_converter, prefix, definition_cls)

Bases: object

convert(tensor_var, pragma='partition')
class hls4ml.backends.fpga.fpga_types.BramWeightVariableConverter

Bases: object

classmethod convert(weight_var)
class hls4ml.backends.fpga.fpga_types.CompressedTypeConverter

Bases: hls4ml.backends.fpga.fpga_types.TypeDefinition, hls4ml.backends.fpga.fpga_types.TypePrecisionConverter

convert_precision(precision_converter)
definition_cpp()
class hls4ml.backends.fpga.fpga_types.ExponentTypeConverter

Bases: hls4ml.backends.fpga.fpga_types.TypeDefinition, hls4ml.backends.fpga.fpga_types.TypePrecisionConverter

convert_precision(precision_converter)
definition_cpp()
class hls4ml.backends.fpga.fpga_types.FixedPrecisionConverter(type_map, prefix)

Bases: hls4ml.backends.fpga.fpga_types.PrecisionConverter

convert(precision_type)
class hls4ml.backends.fpga.fpga_types.HLSTypeConverter(precision_converter)

Bases: object

convert(atype)
class hls4ml.backends.fpga.fpga_types.InplaceVariableConverter(type_converter, prefix)

Bases: object

convert(tensor_var, io_type)
class hls4ml.backends.fpga.fpga_types.NamedTypeConverter

Bases: hls4ml.backends.fpga.fpga_types.TypeDefinition, hls4ml.backends.fpga.fpga_types.TypePrecisionConverter

definition_cpp()
class hls4ml.backends.fpga.fpga_types.PackedTypeConverter

Bases: hls4ml.backends.fpga.fpga_types.TypeDefinition, hls4ml.backends.fpga.fpga_types.TypePrecisionConverter

definition_cpp()
class hls4ml.backends.fpga.fpga_types.PrecisionConverter

Bases: object

convert(precision_type)
class hls4ml.backends.fpga.fpga_types.PrecisionDefinition

Bases: object

definition_cpp()
class hls4ml.backends.fpga.fpga_types.QuartusArrayVariableConverter(type_converter)

Bases: hls4ml.backends.fpga.fpga_types.ArrayVariableConverter

class hls4ml.backends.fpga.fpga_types.QuartusArrayVariableDefinition

Bases: hls4ml.backends.fpga.fpga_types.VariableDefinition

definition_cpp(name_suffix='', as_reference=False)
class hls4ml.backends.fpga.fpga_types.QuartusInplaceVariableConverter(type_converter)

Bases: hls4ml.backends.fpga.fpga_types.InplaceVariableConverter

class hls4ml.backends.fpga.fpga_types.QuartusStructMemberVariableConverter(type_converter)

Bases: hls4ml.backends.fpga.fpga_types.StructMemberVariableConverter

class hls4ml.backends.fpga.fpga_types.QuartusStructMemberVariableDefinition

Bases: hls4ml.backends.fpga.fpga_types.VariableDefinition

definition_cpp(name_suffix='', as_reference=False)
class hls4ml.backends.fpga.fpga_types.StaticWeightVariableConverter(type_converter)

Bases: object

convert(weight_var)
class hls4ml.backends.fpga.fpga_types.StaticWeightVariableDefinition

Bases: hls4ml.backends.fpga.fpga_types.VariableDefinition

definition_cpp(name_suffix='', as_reference=False)
class hls4ml.backends.fpga.fpga_types.StreamVariableConverter(type_converter, prefix, definition_cls)

Bases: object

convert(tensor_var, n_pack=1, depth=0)
class hls4ml.backends.fpga.fpga_types.StructMemberVariableConverter(type_converter, prefix, definition_cls)

Bases: object

convert(tensor_var, pragma='partition', struct_name=None)
class hls4ml.backends.fpga.fpga_types.TypeDefinition

Bases: object

definition_cpp()
class hls4ml.backends.fpga.fpga_types.TypePrecisionConverter

Bases: object

convert_precision(precision_converter)
class hls4ml.backends.fpga.fpga_types.VariableDefinition

Bases: object

definition_cpp(name_suffix='', as_reference=False)
class hls4ml.backends.fpga.fpga_types.VivadoArrayVariableConverter(type_converter)

Bases: hls4ml.backends.fpga.fpga_types.ArrayVariableConverter

class hls4ml.backends.fpga.fpga_types.VivadoArrayVariableDefinition

Bases: hls4ml.backends.fpga.fpga_types.VariableDefinition

definition_cpp(name_suffix='', as_reference=False)
class hls4ml.backends.fpga.fpga_types.VivadoInplaceVariableConverter(type_converter)

Bases: hls4ml.backends.fpga.fpga_types.InplaceVariableConverter

class hls4ml.backends.fpga.fpga_types.VivadoStreamVariableConverter(type_converter)

Bases: hls4ml.backends.fpga.fpga_types.StreamVariableConverter

class hls4ml.backends.fpga.fpga_types.VivadoStreamVariableDefinition

Bases: hls4ml.backends.fpga.fpga_types.VariableDefinition

definition_cpp(name_suffix='', as_reference=False)

Module contents